Go from AI and product ideas to evidence in weeks. We help you validate fast, stop the wrong ideas early, and make decisions with data, not opinions.

Join 3,000+ pretotypers, product leaders, and experimenters getting hands-on tactics for rapid experimentation. Not theory, real techniques you can use this week.

The Real Goal: Finding the Best Ideas to Invest In

Experimentation is great, but what you’re really looking for is the best ideas to invest in. The goal is to run as many experiments as possible as fast as possible to reduce your time to data, while still keeping the human element and diversity of thinking. Gather ideas, prioritize, design experiments, run them, get feedback, and make decisions.

We’ve been exploring how to compress each of these steps using new AI capabilities, drawing on thousands of experiments we’ve run and the body of knowledge based on pretotyping.

Compressing Each Step of the Innovation Process

Let’s break this down step by step to see how we can speed up each stage.

1. Compress the brainstorming

We’ve been experimenting with a tool to generate quality, reasonably unique ideas based on understanding your company, your competitors, and your strategic goals. It can generate 10, 20, 50, or even 100 reasonably good ideas, which then go straight into the platform for evaluation.

2. Augment the prioritisation step

This is still a judgment call for your teams to prioritise, but we built a tool to quickly assess the idea. it’s still in the pretotype phase, but you can try it here. I’d love your feedback.

3. Speed up the Exploration phase

This is where the AI tools have really been effective. We’ve used our knowledge from thousands of experiments and Lean Canvases we’ve built to embed best practices for doing pretotyping and rapid experimentation at scale in the real world, while considering risk, governance, and legal constraints, of course with fully anonymised data. We’re able to take a first pass at evaluating your idea, generate a Lean Canvas, and suggest a reasonable XYZ hypothesis. It’s still a work in progress, but it’s exciting to see how we can make this go faster for you.

4. Get to experimenting as fast as possible

We’re also experimenting with a tool to recommend and suggest experiments for your particular business, its stage, and what you’re trying to learn. And we’re getting really good results from this. So watch this space.

5. Build and run the experiments

Up until now, with the variety and complexity of customers we’ve worked with, we haven’t run experiments on their behalf and we might still not do that. And that is often a bottleneck on how to get access to resources and engineering talent. But with the advent of AI we’ve been testing how you can spin up quality safe experiments within a day or two. They conform to brand, risk, and compliance, and we get them out the door fast.

Spotted in the Wild

I’ve been eating my own dog food. Here’s what I built over the past 8 weeks experimenting with Claude Code:

1. Exponentially Platform re-platforming (37 hours)

Consolidated and rebuilt the entire platform with AI-accelerated features.

2. Custom time management system (22 hours)

100% tailored to my workflow instead of settling for 80% SaaS solutions.

3. Property research automation (2 hours)

Built on a Friday night. Auto-generates research summaries for property inspections, tracks preferences, and surfaced pre-inspection details we never would have found manually.

4. Pipedrive sales bot

Connects Claude to our CRM. Summarises deals, drafts follow-ups, flags stale opportunities. Replaced manual pipeline reviews.

5. Claude Ralph (open source)

Autonomous AI development loop for Claude Code. Runs overnight and builds features without manual intervention. github.com/LeslieCBarry/claude-ralph

The So What: $80,000 to $90,000 Saved

By my estimate, I’ve saved about $80,000 to $90,000 by doing this. That’s real money that would have gone to SaaS subscriptions and development costs, and ongoing cost-avoidance for 2026.

How to Get Started

So how do you activate this? What’s your next experiment?

Have a look at all the services that you use and ask AI to brainstorm with you on the parts that you actually use, not the 80% that you don’t. See if you can build that yourself.

The space is moving fast, so get your hands on the tools, whatever your role. You’ll be amazed.

A quick example: I’ve fully replaced Zapier, Rebrandly, and multiple other tools by building exactly what I needed.

Tool of the Month

Claude Code

After 20 years away from coding, Claude Code has reminded me that everything is code. If you’re not doing this, you’re missing a superpower to accelerate your understanding of what’s possible. I’ve shipped more working tools and platform updates this month than we did in the last year.

https://github.com/LeslieCBarry/claude-ralph

Here’s my best tip from the past few weeks: I found and tested a way to build features autonomously with a self-improvement loop. The tool is called Ralph, and it’s been incredibly useful. I modified it to use Claude Code instead of AMP, and it ran flawlessly, building a new feature in just a few hours.

Thanks to Greg Isenberg and Ryan Carson for getting this walkthrough out there so fast. Follow them if you want actionable, practical tips and tools in this space.

Find the Best Ideas to Invest In

I work with teams to go from ideas to evidence in weeks. We embed rapid experimentation using pretotyping as a core capability to validate fast, stop the wrong ideas early, and invest in the winners.

👉 If you want to hear more about how we do this, happy to do a 15 or 30 min free call. Just reply.

👉 If you’d like to try any of these tools I’ve mentioned in their current pretotyping state, reach out and I’m happy to share the links with you.

“Run as many experiments as possible as fast as possible to reduce your time to data.”

Until next month, happy innovating!

Leslie

Back then, that obsession helped Microsoft beat Apple and dominate the market.

Today, the stakes are even higher — because "developers" isn't a niche anymore.
Product managers, marketers, ops, founders, analysts. Anyone who can prompt an AI and ship workflows, scripts, and tools is effectively a developer. The developer market is 100–1000x bigger than it was in Ballmer's era.

I was writing code and attending Tech-ed conferences in the early 2000s. What I'm seeing now feels like that same inflection point — except the tent is massively bigger.

And I'm not just observing it — over the past 8 weeks, Claude Code has become my dev team. I've shipped more working tools and platform updates this month than we did in the last year.

That's why Claude Code is winning right now:

• Removes friction from making things that actually work

• Opinionated about real workflows, not generic chat

• Built for people who ship, not people who "explore AI"
  
  OpenAI is still very much in the game, but it's currently too general-purpose. Codex is fine, but Claude Code feels built for the new reality where everything is code and everyone is writing it — whether they realise it or not.
  

  The next platform winners won't just serve developers. They'll create them.
  

Two Adams Walk Into a Bar (Well, Almost)

Last month we pretotyped a live LinkedIn webinar with two Adams.

Adam Murphy, a human-centered strategy expert. Adam Norris, a design and prototyping specialist. And me—eight years deep into pretotyping at scale.

The format was simple: let’s talk about what makes pretotyping different from prototyping, and why the distinction actually matters.

What I didn’t expect was how much the conversation would clarify something I’ve been wrestling with for years: why do smart teams keep jumping straight to “can we build it?” before answering “should we build it?”

My Job Is to Stop People Getting to Your Job

About 15 minutes in, Adam Norris asked me how I got into pretotyping.

I told him the truth: through building startups, failing at most of them, and getting really frustrated that we kept spending time and money building things nobody wanted.

Adam’s a prototyper. He makes physical products real. He helps teams test whether they can build something, whether it works, what it costs.

My job is to stop people taking bad ideas to Adams job.

But if I can help teams figure out should we even bother before they get to Adam, we save time, money, and a lot of heartbreak.

That’s the difference:

• Prototyping asks: “Can we make this thing?”

• Pretotyping asks: “Should we bother to make this in the first place?”

And here’s the kicker: most organizations skip pretotyping entirely. They go straight from idea to prototype to MVP—without ever testing if customers actually care.

↓ Watch this 2-minute clip to hear how I went from failed startups to falling in love with Alberto Savoia’s approach.

The MVP Trap

Adam Murphy asked the question everyone asks:

“Is a pretotype the same as an MVP?”

Absolutely not.

Here’s what’s happening right now in innovation: someone has a brain wave, they vibe-code a thing using AI, and they put it out there. They’ve skipped the most important step: does anybody care?

An MVP is build-measure-learn. You build something minimal, measure how people use it, learn from that.

Pretotyping is learn-measure-build. You learn if there’s a problem worth solving, you measure actual customer behavior (not opinions), and then you build.

I gave them a recent example: I worked with a crypto exchange last month. Their first pretotype wasn’t code—it was Intercom. We put a value proposition in front of 100 customers, asked them a question, measured if they engaged.

Fast. Cheap. Data over opinion.

And here’s the uncomfortable truth I shared: Sadly for everybody listening, mostly nobody cares. No one’s interested. All your ideas are bad. Nobody cares about your stupid idea.

It’s very difficult to get any level of interest. So you need to test fast and cheap to find out which ideas actually have legs.

↓ Watch this 3-minute clip for the full breakdown of pretotyping vs prototyping vs MVP (including the crypto exchange example).

Spotted in the wild:

Three insights from the conversation that you can apply immediately:

1. Disconnect the idea from the person

Traditionally, we pitch ideas like this: “I’ve got this awesome idea, I’m putting my career on it, give me money.” Then if it fails, someone’s in trouble.

Instead: test ideas as a team, from the customer perspective. Run structured experiments where you agree upfront what “good” looks like. When customers don’t engage, it’s not personal failure—it’s rapid learning.

2. Low fidelity gets better feedback

Adam Norris made a great point: when you show people a polished prototype and ask “what do you think?” they say “that’s pretty good.”

But when you show them a pencil sketch or Play-Doh wrapped around another product, they give you real feedback: “It’s too tall,” “Why purple?” “We don’t need another soft drink.”

Lo-fi isn’t a weakness—it’s a feature. It invites honest critique.

3. The right question defines the right prototype

Not every test needs to be high fidelity. If you’re testing whether bar layout improves customer flow, build it out of Corflute (which I did for Anheuser-Busch InBev in Boston).

You don’t need feedback on aesthetics. You need feedback on flow. Match your fidelity to your question.

The 60-Day Product Launch

Adam Norris shared one of my favorite examples: Carlton United Breweries launching their first seltzer in 60 days—from idea to shelf.

How? They ran a Design Sprint. Marketing, agency, decision-makers all in one room. Adam’s team brought prototypes to life in real-time—3D printing different can shapes, printing new labels, testing with consumers iteratively over three days.

Meanwhile, the technical team was in the kitchen changing flavor proportions based on live feedback. “Too much vodka? Add less.” “Lime needs mint? Let’s try it.”

They didn’t answer every final detail in those three days. But by iterating so quickly, they compressed months of work into 60 days.

The breakthrough? Asking “what would have to be true?” instead of “why can’t we?”

↓ Watch this 3-minute clip to hear Adam walk through the full Carlton United Breweries story.

Why Innovation Leaders Last 18 Months

Toward the end, I shared something I’ve researched on LinkedIn:

The average lifespan of an innovation leader is 18 months.

Why? Because they don’t build sustainable systems. They rely on champions pushing upstream against an organization designed for stability and repeatability.

If that’s true, you can’t fight the system. You need to work with it. Create something the system recognizes.

I learned this firsthand when I took four customers on what became the “Global Pretotyping Summit” in 2019. We visited CES in Vegas, then toured Google, Facebook, and other Silicon Valley companies. Seeing Facebook run 10,000+ experiments concurrently—releasing features automatically based on data—was a wake-up call. The companies that scale innovation don’t rely on heroes. They have systems.

↓ Watch this 2-minute clip about how the “Global Pretotyping Summit” accidentally became real.

That’s why we built Rapidly—a platform to manage ideas and experiments at scale. Because running 5–10 experiments a year is a waste of time. If 90% of ideas fail, you need to run hundreds of experiments to find the winners.

And that only works when you have a system.

How to Get Started

Both Adams had great advice for people wanting to build this muscle:

From Adam Norris (prototyping):

Get hands-on. Buy a competitor product, mold Play-Doh onto it, scan it with your phone’s free 3D scanning app, change the label, reprint it. You can get a rough prototype in under an hour.

Prototyping has never been more accessible. The tools are there. The question is: can you make time for it?

From me (pretotyping):

Read Alberto Savoia’s book The Right It. Take my free pretotyping course on YouTube. Download Rapidly and try it. Join our Slack community (850+ people from around the world).

But most importantly: just do it.

You’ve got that idea that’s been bothering you for a year. Whip up a website. Put it out there. See what happens. Learn.

Don’t be scared to fail. You’re going to fail 100%. But the outcome of failure is learning.

↓ Watch this 4-minute clip for practical tips on getting started with prototyping—even with zero tech skills.

The Bottom Line

If you knew it would take 20 failures to make a $100 million product, how fast would you want to fail?

As fast as you possibly can.

That’s pretotyping. That’s prototyping. That’s rapid experimentation.

The only way to beat the default outcome—which is failure—is to fail faster, cheaper, and smarter than everyone else.

Full conversation: ↓ Watch the uncut version, including stories about the accidental Global Pretotyping Summit, how Facebook runs 10,000 experiments a day, and why getting bad feedback on a prototype is actually the goal.

Tool of the Month

Claude Code + Windsurf Editor

I’ve been experimenting with Claude paired with Windsurf Editor, and it’s changing how fast I can prototype digital products. Think of it as having an AI pair programmer who can write, test, and iterate code in real-time—perfect for rapid pretotyping of software ideas. If you’re testing digital concepts, this combo lets you go from idea to working prototype in hours, not days.

Build the System to Test Ideas Fast

Stop wasting months on AI and Product ideas nobody uses. I work with teams to embed rapid experimentation using pretotyping as a core capability to test ideas fast, kill the losers early, and invest in the winners—in weeks, not quarters.

I run complimentary executive briefings and team sessions online. It’s a quick 30-minute intro to Pretotyping, real case studies, and how to test which ideas need validation before investment.

Book your free briefing

“Prototyping asks ‘can we make it?’ Pretotyping asks ‘should we bother?’ Most teams skip the second question—and that’s why most ideas fail.”

I can’t share the company name, but I can share the playbook.

Inside a multi-billion-dollar, highly regulated organisation, a small innovation team faced the classic challenge: how do you move fast when every decision needs approval, when compliance is non-negotiable, and when “just try it” isn’t an option?

They didn’t ask for permission to move faster. Instead, they partnered with Legal and Risk from day one. They embedded Pretotyping as the method for turning opinion into evidence. And they built safe-to-fail guardrails that could be reused across multiple experiments.

The transformation was remarkable.

What used to be “opinion shipping” — building features based on what stakeholders thought customers wanted — became an evidence-led Innovation Engine. Those retail touchpoint screens that everyone assumed were just “noise”? They became measurable conversion channels. Time from idea to first experiment? Down to about 8 days.

In roughly 12 months, they ran over 130 live experiments.

But the real win wasn’t the volume. It was the shift in decision quality. Leaders started trusting the process because experiments consistently answered “Should we build this?” before anyone wasted time on “How do we build this?”

What made it work

Three things stood out:

1. They partnered with Legal and Risk early — not as gatekeepers, but as experiment design partners. Getting permission frameworks upfront meant velocity later.

2. They ran concurrent experiments — patterns across multiple tests improved their selection quality. What worked in one channel informed tests in three others.

3. They prioritised speed over perfection — imperfect experiments that shipped in 8 days beat perfect plans that took months.

Read the full Case Study

The takeaway: Velocity without validated ideas is just fast failure. Pretotyping gives you both.

What happens when AI runs your customer interviews?

An unexpected experiment with voice AI that changed how we capture customer stories — and a case study from inside a regulated giant.

The AI Interviewer Experiment

Last month, I tried something I wasn’t sure would work: I let ChatGPT’s voice mode conduct a customer case study interview.

I’ve done hundreds of these interviews over the years, and I know the patterns: you ask a question, the interviewee starts answering, you’re already thinking about your next question, and suddenly you’ve missed the most important thing they just said. Then you’re scrambling to redirect the conversation back to what mattered.

But when I handed the facilitation to ChatGPT, something shifted.

The AI asked one question at a time. It held context perfectly. When someone gave a surface-level answer, I could prompt the AI mid-conversation: “Ask for a concrete example” or “That’s interesting, dig deeper there.” The AI adapted instantly, without the awkward conversational resets that happen when humans try to course-correct.

The result? A coherent, quote-ready narrative in one sitting. Less “wait, where were we?” and more focused storytelling from the person being interviewed.

Why this matters

Better interviews mean faster case studies, cleaner proof points for executives, and more useful enablement content. The quality of your customer stories directly impacts how quickly you can share proof of value across your organisation.

How to try it yourself

1. Brief the AI on your goal and any guardrails.

2. Ask it to keep single-question pacing (one question, wait for answer, then next)

3. Stay in the conversation to prompt follow-ups: “ask for a concrete example” or “summarise what they’ve said and move on”

Read the full AI-facilitation playbook

Spotted in the wild:

Three things from this month that you can apply immediately:

1. Time to first experiment beats time to perfect experiment

Stop debating the perfect test design. Ship something in 8 days. Learn from real data. Adjust. Repeat.

2. Partner with Legal and Risk before you need them

The teams that move fastest in regulated environments aren’t the ones who avoid compliance — they’re the ones who build reusable approval frameworks early.

3. Concurrent experiments compound learning

One test gives you one data point. Three tests running in parallel reveal patterns. Those patterns improve your ability to choose what to build next.

Building experiment velocity in your company? I work with leadership teams to embed rapid experimentation as a core capability, increasing confidence in investing in the right products. Reply if you want to explore what this looks like for your business.

One thing

Running a retrospective this month? Try this:

Copy your sticky notes into Claude or ChatGPT and prompt: “Group and label these into themes. Output a concise summary with next-step recommendations.”

I’ve been using this after team sessions, and it’s a 10x lift in clarity and speed. What used to take 20 minutes of manual clustering now happens in seconds, and the AI often spots patterns I missed.

Tool of the Month

Notion AI

I’m late to the Notion party. Now that everything lives here, Notion AI is the tool I didn’t know I needed. It has context across my whole workspace — case studies, client notes, past experiments, drafts — so it can spot patterns, pull the right snippet, or resurface that one insight without me copy‑pasting. The ability to edit and iterate in real-time on a document is 10 times faster. It’s smarter because it knows what I know. This is what Gemini should be doing in Docs, Sheets, and Gmail.

Get Started with Your Innovation Engine

I run complimentary executive briefings and team sessions online, so you can join in wherever your team is based. It is a quick 30-minute talk to introduce Pretotyping, share real case studies, and show how to test which AI and innovation ideas need validation before investment.

👉 Just reply to this email if you’d like to set one up.

Last week, I had the chance to speak at Mantel Group’s AI Innovation Day, and I opened with a provocation:

If AI lets us go straight from idea to vibe-coded proof of concept, does that mean experimentation is dead?

The answer is no. AI accelerates the build — but it doesn’t replace the fundamentals. We still have to ask the right questions, test with real customers, and let evidence guide our bets. That’s the heart of innovation.

What I Shared

• Evidence beats opinion every time. We’ve seen companies save millions by shelving the wrong ideas early, while generating new value from the right ones.

• AI is a game-changer. It accelerates everything: idea generation, coding, prototyping, testing. The real advantage isn’t just faster builds, but faster learning.

• The Innovation Engine matters more than ever. Start by learning the methods, accelerate with 2–4 week sprints, and sustain by embedding the capability into your teams.

Proof in Action

In the session I shared some real examples:

• An early project at SwiftX that was shelved → hundreds of thousands saved

• A failed AI concept that could have cost millions → stopped before launch

• An AI initiative validated with strong ROI → significant upside

• Another scaled AI experiment with a large customer → multi-million dollar value created

The message landed: winning with AI isn’t about having the boldest ideas, it’s about testing more ideas, faster, and only scaling what customers actually prove they want.

My Takeaway

Standing in front of a room of leaders grappling with AI’s potential, I was reminded that the fundamentals haven’t changed: innovation equals experimentation equals results. AI just makes it possible to do this at a speed and scale we’ve never had before.

👉 If you’re curious about how this applies in your context, the best place to start is with our Innovation Engine Playbook.

Now Free: Pretotyping Course on YouTube

When I first learned Pretotyping from Alberto Savoia, it completely changed how I thought about innovation. It’s the foundation of data-driven experimentation, and I believe it should be a baseline skill for every innovator.

That’s why I’ve made my complete $400 Pretotyping course free on YouTube. Not as a marketing play, but because I want more people using Pretotyping to test ideas with evidence, not assumptions.

Here’s what’s inside:

• Foundations of Pretotyping – what it is and why it matters

• The Innovator’s Mindset – how to escape “Thoughtland” and kill bad ideas early

• The Pretotyping Toolkit – practical methods like Fake Door and Mechanical Turk

• From Idea to First Experiment – structuring assumptions and launching your first test

• Running Experiments & Getting Data – designing pretotypes and getting the evidence you need

Hopefully, this is a small step toward more teams building what customers actually want.

👉 Start with Module 1 on YouTube

Building experiment velocity in your company? I work with leadership teams to embed rapid experimentation as a core capability, increasing confidence in investing in the right products. Reply if you want to explore what this looks like for your business.

Tool of the Month

Aqua Voice
I have been using Aqua Voice on Mac to work with Claude, ChatGPT, and Gemini without typing. It is context-aware, so it adapts whether you are in email, Slack, or Asana. After trying WhisprFlow and Talktastic, this is the one that stuck.

Get Started with Your Innovation Engine

I run complimentary executive briefings and team sessions online, so you can join in wherever your team is based. It is a quick 30-minute talk to introduce Pretotyping, share real case studies, and show how to test which AI and innovation ideas need validation before investment.

👉 Book your free session here

The results blew me away.

24 ideas captured. 12 experiments designed and run. 500+ customers engaged.

But the real transformation wasn't in the numbers; it was watching a team shift from "let's build this" to "let's test if anyone wants this."

Let me share what made the difference.

Leslie

Spotted in the wild:

Three things about building experiment velocity that you can apply immediately:

1. Time to first experiment beats time to perfect experiment

The team's first experiment was clunky. Tracking wasn't perfect. The message could have been clearer.

They launched it anyway.

Result: 20% engagement rate on their very first try.

The insight? Getting data from real customers in week one taught them more than another month of planning would have. Speed creates learning momentum that perfectionism kills.

2. "Data over opinion" becomes cultural DNA

By week 3, something shifted. Instead of debating whether customers would want a feature, they'd say "let's test it."

One experiment failed at 15% when they added pricing. Instead of defending the idea, they immediately started designing the next test.

The magic happens when teams stop being precious about their ideas and start being curious about customer behaviour.

3. Concurrent experiments compound learning

Weeks 1-2: One experiment at a time Weeks 3-4: 2-3 experiments running simultaneously

The breakthrough wasn't just running more tests—it was seeing patterns across experiments. What worked for monthly subscriptions also worked for security features. Customer psychology insights from one test informed three others.

Parallel experimentation creates a learning flywheel that single tests can't match.

The bottom line:

Most teams I work with are stuck in analysis paralysis. They want the perfect experiment, the perfect message, the perfect everything.

This team proved something different: imperfect experiments that ship fast beat perfect experiments that ship slow.

The 4-Week Rapid Experimentation Sprint:

Here's exactly how we transformed a team from zero experiments to running 3 concurrent tests:

Week 1: Foundation training and first experiment launch

- Rapid Experimentation using Pretotyping One-Day Workshop

- Lean Canvas workshops to capture customer perspective

- First Pretotyping hypothesis designed and live within 2 days

- Team learns "data over opinion" mindset

Week 2-3: Scale to multiple experiments

- 2-3 experiments running simultaneously

- Daily check-ins and experiment design workshops to replace endless planning meetings

- Focus shifts from perfection to velocity

Week 4: Results and sustainable process

- Retrospective on what worked (and what didn't)

- Framework for ongoing experimentation

- Team equipped to continue without external support using Rapidly software.

The outcome? A sustainable innovation engine that runs experiments as business-as-usual, not special projects.

Want to build this muscle in your team?

The framework is simple:

1. Start with customer problems, not solutions

2. Test one variable at a time

3. Set clear pass/fail criteria upfront

4. Launch in 8 days maximum

5.Learn, adjust, repeat

But simple doesn't mean easy. It requires shifting from "build first, validate later" to "validate first, build smart."

That's the cultural transformation that creates sustainable innovation velocity.

One thing

I used Ideaboardz for the retro, copied it into Claude.ai during the live session and prompted

‘we're running a brainstorm session to retro the rapid sprint project at [clientname]. Group and cluster these ideas’.

Instant 10x gain on time and quality of output.

Tool of the month:

After years of task management overload, I've finally found my solution in Akiflow.

I was drowning in Sunsama, Asana, Slack, Trello, starred emails, Pipedrive, and countless task lists. Akiflow brings everything into one view with tasks and calendar unified. This single source of truth has dramatically reduced my overwhelm and brought clarity to my daily planning. Game changer for my workflow!

Test your ideas using Rapidly.

Get the Playbook

Two weeks ago, Patrick Smith and I ran an experiment to see if we could use ChatGPT in voice mode to facilitate a case study discussion, preloaded with all the context, frameworks, and goals.
It has completely changed how I think about running sessions.

Imagine a brainstorming session or case study interview where no one is stuck facilitating, and the conversation flows seamlessly.

The results?

Within 15 minutes, we had forgotten we were even talking to an AI.

AI guided the discussion, allowing for natural meandering and bringing us back on track when needed.

By the end, it had generated three tailored case study drafts (focused on change management, risk, and outcomes).

This approach not only saved time but also preserved valuable organisational knowledge and created actionable artifacts in real-time.

Practically, I'm finding that AI is most useful in the experimentation process, as it helps facilitate collaboration on improving the quality of thinking at each stage and removes friction from the actual running of experiments.
*Case study coming soon.

How are you leveraging it to rethink your experiment workflows?

Subscribe now

For the past two years, I've been using Fireflies.ai to transcribe my MS Team's, Google Meet and Zoom calls. I have hundreds of transcripts BUT Fireflies has no bulk download capability. I often run these transcripts through ChatGPT to summarise project discussions or mine them for workshop improvements that I can make. My solution was to ask my VA to download the files manually and work from there.

I’m working on a project that requires 40 to 50 files, so I needed an alternative to my VA.

Enter Claude.AI

To solve this problem, I asked Claude to suggest options. Claude suggested a Python script 👀 (despite having zero Python experience). Working on my Mac, Claude guided me through multiple iterations over about 45 minutes until we had a working solution for automatic bulk downloads. While this automation has made my virtual assistant's transcription management role redundant, it's solved my problem, saved me money and paid for my Claude, ChatGPT and Fireflies subscription!

The script has been performing excellently, and I wanted to share it with you. Try it out and let me know if you discover any bugs or potential improvements.

Here are the complete step-by-step instructions to download your Fireflies.ai transcripts:

1. Initial Setup (one-time only):

bash
# Create directory 
mkdir fireflies_downloader 
cd fireflies_downloader
 
# Create the Python script 
nano fireflies_downloader.py 

# Get your API key from Fireflies.ai: 
# 1. Log into Fireflies.ai 
# 2. Go to Settings → Developer Settings → API 
# 3. Copy your API key 
# Set your API key in Terminal 
export FIREFLIES_API_KEY="your_api_key_here"
 
# Install required Python package 
pip3 install requests

2. Script Content:

• Open fireflies_downloader.py

• Press Control + K repeatedly to clear any existing content

• Paste the full script into fireflies_downloader.py

import requests
import json
import os
from datetime import datetime, timedelta
import time

class FirefliesDownloader:
    def __init__(self, api_key):
        self.api_key = api_key
        self.base_url = "https://api.fireflies.ai/graphql"
        self.headers = {
            "Authorization": f"Bearer {self.api_key}",
            "Content-Type": "application/json"
        }
    
    def get_transcript_content(self, transcript_id):
        """
        Fetch detailed content for a specific transcript
        """
        query = """
        query GetTranscriptContent($id: String!) {
            transcript(id: $id) {
                title
                id
                transcript_url
                duration
                date
                participants
                sentences {
                    text
                    speaker_id
                    start_time
                }
                summary {
                    keywords
                    action_items
                }
            }
        }
        """
        
        variables = {
            "id": transcript_id
        }
        
        try:
            print(f"Fetching content for transcript {transcript_id}...")
            response = requests.post(
                self.base_url,
                headers=self.headers,
                json={"query": query, "variables": variables}
            )
            
            if response.status_code != 200:
                print(f"Error getting transcript content: {response.status_code}")
                print(response.text)
                return None
                
            data = response.json()
            if "errors" in data:
                print("API returned errors:", json.dumps(data["errors"], indent=2))
                return None
                
            return data["data"]["transcript"]
            
        except requests.exceptions.RequestException as e:
            print(f"Error fetching transcript content: {e}")
            return None

    def get_transcripts(self, limit=25, to_date=None):
        """
        Fetch list of transcripts with date filtering
        """
        query = """
        query GetTranscripts($limit: Int, $toDate: DateTime) {
            transcripts(limit: $limit, toDate: $toDate) {
                title
                id
                transcript_url
                duration
                date
                participants
            }
        }
        """
        
        variables = {
            "limit": min(limit, 25),
            "toDate": to_date.strftime("%Y-%m-%dT%H:%M:%S.000Z") if to_date else None
        }
        
        try:
            print(f"Making API request for transcripts up to date {to_date if to_date else 'now'}...")
            response = requests.post(
                self.base_url,
                headers=self.headers,
                json={"query": query, "variables": variables}
            )
            
            data = response.json()
            if "errors" in data:
                print("API returned errors:", json.dumps(data["errors"], indent=2))
                return None
                
            return data
            
        except requests.exceptions.RequestException as e:
            print(f"Error fetching transcripts: {e}")
            return None

    def save_transcripts(self, output_dir="transcripts", to_date=None):
        """
        Save all transcripts with their content
        """
        if not os.path.exists(output_dir):
            os.makedirs(output_dir)
        
        # Get existing transcripts to avoid duplicates
        existing_files = set()
        existing_ids = set()
        for filename in os.listdir(output_dir):
            if filename.endswith('.json'):
                existing_files.add(filename)
                try:
                    with open(os.path.join(output_dir, filename)) as f:
                        data = json.load(f)
                        existing_ids.add(data['id'])
                except:
                    pass
        
        last_date = to_date or datetime.now()
        while True:
            result = self.get_transcripts(limit=25, to_date=last_date)
            if not result or "data" not in result or "transcripts" not in result["data"]:
                print("No more transcripts found or error in API response")
                break
                
            transcripts = result["data"]["transcripts"]
            if not transcripts:
                print("No more transcripts found")
                break
                
            print(f"\nFound {len(transcripts)} transcripts")
            
            earliest_date = None
            for transcript in transcripts:
                # Skip if we already have this transcript
                if transcript['id'] in existing_ids:
                    print(f"Skipping existing transcript: {transcript['title']}")
                    continue
                
                print(f"\nProcessing: {transcript['title']}")
                
                # Get detailed content
                content = self.get_transcript_content(transcript['id'])
                if content:
                    transcript = content  # Replace with full content
                
                # Save the file
                date_obj = datetime.fromtimestamp(int(transcript["date"]) / 1000)
                safe_title = ''.join(c for c in transcript['title'] if c.isalnum() or c in (' ', '-', '_', '.'))
                filename = f"{date_obj.strftime('%Y-%m-%d')}_{safe_title[:50]}.json"
                
                filepath = os.path.join(output_dir, filename)
                
                with open(filepath, 'w', encoding='utf-8') as f:
                    json.dump(transcript, f, indent=2, ensure_ascii=False)
                
                print(f"Saved transcript: {filename}")
                
                # Track earliest date we've seen
                if earliest_date is None or date_obj < earliest_date:
                    earliest_date = date_obj
                
                time.sleep(1)  # Be nice to the API
            
            if earliest_date:
                # Subtract 1 second to avoid getting the same transcript again
                last_date = earliest_date - timedelta(seconds=1)
                time.sleep(1)  # Extra pause between batches
            else:
                break

def main():
    api_key = os.getenv("FIREFLIES_API_KEY")
    if not api_key:
        print("Please set your FIREFLIES_API_KEY environment variable")
        return
    
    print(f"Using API key: {api_key[:5]}...{api_key[-5:]}")
    
    # Find the earliest date from existing files
    earliest_date = None
    if os.path.exists("transcripts"):
        files = os.listdir("transcripts")
        if files:
            try:
                for file in files:
                    if file.endswith('.json'):
                        with open(os.path.join("transcripts", file)) as f:
                            data = json.load(f)
                            date = datetime.fromtimestamp(int(data["date"]) / 1000)
                            if earliest_date is None or date < earliest_date:
                                earliest_date = date
                
                if earliest_date:
                    print(f"Starting from before date: {earliest_date}")
            except Exception as e:
                print(f"Error reading files: {e}")
    
    downloader = FirefliesDownloader(api_key)
    downloader.save_transcripts(to_date=earliest_date)

if __name__ == "__main__":
    main()

4. Save with Control + X, then Y, then Enter

3. Running the Script:

bash
# Navigate to the directory (if you're not already there) 
cd fireflies_downloader 

# Run the script 
python3 fireflies_downloader.py

4. What to Expect:

• First run will download the most recent transcripts

• Each subsequent run will fetch older transcripts

• Script will automatically:

  • Skip duplicates

  • Show progress

  • Create a 'transcripts' folder

  • Save each transcript as a JSON file named with date and title

5. To Get More Transcripts:

• Just run the script again

• Keep running until you see "No more transcripts found"

• Each run will go further back in time

6. Files Location:

• All transcripts are saved in the transcripts folder

• Files are named like: YYYY-MM-DD_Title.json

• Each file contains:

  • Full conversation text

  • Speaker information

  • Summary and keywords

  • Meeting metadata

7. Troubleshooting:

• If you get "API key not found" error:

bash
export FIREFLIES_API_KEY="your_api_key_here"

• If you close Terminal and come back later:

bash
cd fireflies_downloader 
export FIREFLIES_API_KEY="your_api_key_here" 
python3 fireflies_downloader.py

8. Best Practices:

• Run during off-peak hours

• Let each run complete

• Keep the script and files for future use

• Make backups of your transcripts folder

The script is designed to be safe to run multiple times - it won't duplicate downloads and will automatically continue where it left off.

(stay with me here 😁) .

My summary from his Personal Annual review

Review the Year's Calendar: Start by looking at your calendar for the past year. Focus on all the events, meetings, personal activities, and projects.

Categorize Each Activity: Assign a color code to each activity:

Green: Activities that created energy and enthusiasm.

Red: Activities that drained energy or felt taxing.

Yellow: Activities that were neutral, neither particularly energizing nor draining.

Identify Energy Creators: Look for patterns. Which activities, people, or projects appear in green most frequently? These are your Energy Creators.

Document Energy Creators: Write down all these energizing elements. This step is crucial for visualizing and acknowledging what brings you positive energy.

Evaluate Time Allocation: Reflect on how much time you spent with these Energy Creators. Did they receive enough attention and time, or were they overshadowed by energy-draining (red) or neutral (yellow) activities?

Plan for Future Allocation: Based on your findings, consider how you can adjust your schedule in the future to spend more time on activities, people, and projects that energize you.

This process should help you gain insights into what brings you energy and how to optimize your time for a more fulfilling and productive year.

Less Productivity Hacks

The internet is awash with productivity hacks, but it's time to trust that I've learned enough. I've absorbed, considered, and implemented the tips that work for me. It's time to rely on my own judgment and let go of the constant search for new hacks.

Less Software to Solve the Thinking Problem

NoCode platforms have their place, but sometimes they add unnecessary complexity. This year, I'm embracing simplicity and recognizing that not every problem needs a software solution.

Less Investing Time in Future Proofing the Process

While it's important to be prepared for the future, obsessively future-proofing every process is a form of procrastination. I'll be selective in my efforts, focusing on what's truly valuable.

Less Opinions and News from the World and More Trust in My Own

It's easy to get caught up in the echo chamber of news and opinions. This year, I'm choosing to trust my own experiences and knowledge more, challenging my thinking to find truth rather than validation.

Less Reading

Reading is part of my identity, but it's become a form of procrastination. I plan to read less but more intentionally, choosing books that help me learn, grow, or unwind.

Less Relentless Growing

Growth is good, but relentless pursuit of it can be exhausting. I'm taking time to consolidate my knowledge and discard what's not useful.

Less News

The news is filled with negativity and violence. I'm choosing to engage where I can make a difference and accept that my influence is limited.

Less Work, More Play

Post-Covid, I've realized the importance of play. Moving to the ocean has reenergized me, and I'm committed to maintaining a balance between work and leisure.

More Endless Hobbies and Starting to Learn from Scratch

I'm embracing hobbies like guitar and surfing without the pressure of mastery. It's about enjoying the process and the freedom to learn at my own pace.

Less Sitting

After years of working from home, I'm prioritizing movement. More walking, standing, and engaging with people in real life.

Less Control

I'm opening myself up to spontaneity. Random encounters with strangers or friends can be soul-enriching and mentally stimulating.

Less Safety

Predictability can be stifling. I'm choosing the excitement of the unknown over the comfort of the familiar.

Less Thinking

Action trumps overthinking. I'm committed to being more proactive and back to my 'just F do it' philosophy.

Less New Stuff

I'm returning to the basics that work for me: meditation, exercise, good food, and sleep. These are the pillars of my contentment.

Less Measuring

While trackers can be useful, constant monitoring is overkill. I'm focusing on how I feel rather than obsessing over stats.

Less To-Dos

It's time to face reality and trim my to-do lists. I'm focusing on actions that have a positive impact on my life and letting go of the rest.

In essence, this list is not about doing more; it's about doing better. It's about asking the simple questions: Does it make my life better? Is it the simplest solution? Can I do less and get the same outcome? Do I get good energy from this?

Wishing you a year of less, but also, so much more.

I upgraded my Razor Core X eGPU and replaced my Macbook Pro with a Mac Mini for the perfect silent setup. No more noisy, annoying fans spinning up while recording audio.

Working from home for an extended period has made me hyper-aware of everything I can ‘optimise’ in my study. It’s optimised to within an inch of its life, but the final victory was getting my Mac setup silent. I’m using this COVID time to create our first online Pretotyping course, so a quiet environment for recording is a must.

I’ve had a fun time learning all about mics, cameras, recording, lighting, etc., but, as we know, the most important of all is limiting background noise for excellent quality audio.

Enter my trusty Macbook Pro 2018 and Razor Core X eGPU. 
Recording course content is an exercise in patience and clarity, and as you think you’ve nailed it — WHHHHHRRRRR — up spins a fan somewhere. Not happy.

So the journey begins.

Suspect #1: Razor Core X eGPU

The Razor Core X eGPU has two fans, one for extracting air from the case and another on the power supply. After much googling (thanks Reddit and eGPU Forum) I discovered that the main culprit is the power supply fan.

I replaced the power supply with the Corsair 750W SF750 Platinum High Performance SFX Power Supply and the Case Fan with the Noctua NF-F12-PWM 120mm Fan.

Voila! Silence. The PSU fan doesn’t spin up unless under at least 30% load and the case fan is silent. This is important as the eGPU is always on if it’s connected to the Mac and unplugging it every night is a pain.

Suspect #2: MacBook Pro

Next up, my overheating Macbook Pro. I considered an upgrade to the latest one, but — and it’s a big but — I’m an occasional gamer, so I need Bootcamp running, and the latest Macbooks are Intel based but moving over to ARM next year, so it’s wasted money for an end of life technology.

Mac Mini to the rescue!

Enter the Mac Mini. If you compare performance, drive size and memory this is a no brainer. Much better value than an about to be redundant Macbook Pro, the Mac Mini runs Intel for Bootcamp so is future-proofed, and practically a ‘desktop’ so I’ll get 3 to 4 years usage out of it for my use case.

“But Leslie, that’s dumb. It’s not a laptop”. We’re working from home, so all laptops are now desktops.

And, I still have my trusty 2018 MacBook Pro for when we’re out and about again so win-win.

And the result?

Absolute silence. This combo very rarely spins up the fan for work and works beautifully for gaming on Bootcamp.

And as a bonus, it’s neat, simple and tucked away, as good technology should be. Almost invisible.

I like the distinction. When an event like Coronavirus (COVID-19) happens, I grasp for control.

But you can’t control the unknown, so the best alternative is to create order.

Order in our case is an agreed schedule given we’re sharing the same apartment space for a few months without leaving. This was a very good move!

During the week we make sure that we have some time together in the day, but maintain our focus on work and use the time well.

This is an opportunity to “Choose Alive Time or Dead Time. — Robert Greene’.

One of the things we’re doing well is to make space for each other. Two hours of personal time per day. No explanations, no interruptions, no negotiating. Watch TV, work, play, whatever.

We’re also lucky to have a balcony, so the two camping chairs come out quickly when the sun peeks in. We go outside every single day regardless of the weather. First time in twelve years we’ve used the balcony so much!

Also exercise. I have cycled 20 minutes and worked out with over-door exercise cables daily. Who knew I would exercise more being locked up?

The order has been a rock to ensure we communicate well and respect each other’s space. There’s time for play and flexibility, of course, this isn’t the military or prison, but it’s a nice base to work from.

I’m not sure how long this will all go on, but so far we’re not losing it (often) and appreciating the small things we do have. I realise we’re very fortunate and a lot of people are having a really tough time right now, but if you’re grasping for control, try creating some order and relinquishing control for a while. You may be surprised how manageable this can be.

Subscribe now

After a talk on rapid product validation today where I spoke about how companies like Google and Uber focus relentlessly on reducing friction from the existing customer experience as a way to delight them, a member of the marketing team for a large client asked me an interesting question:

How do I find opportunities for innovation? What signals can I look for? How do I spot client friction?

I think a good place to start is to look at the jobs-to-be-done for the customer and count the number of steps it takes to complete the job.

On reflection, it makes sense. Think about a normal taxi ride vs Uber and count the steps from initial contact to destination.

Uber is at least 10x fewer interactions/steps than a traditional taxi. Count them — you’ll be surprised.

I’m going to validate my answer over the next few days and see if it makes sense. On the surface, it seems like a simple way to spot these opportunities.

Books come find me at precisely the moment I need them most.

The good thing about life is someone has been here before us and done most things. And it always helps to go to the source. We only need to open our eyes and ears and listen to their lessons.

I read. A lot. According to Amazon, I’ve averaged 23 days a month this year. It’s my hobby and keeps my mind open to new ideas and thinking. 
Here’s what I read in 2019 and how it’s impacted my thinking. Reading is ok, but it’s also wasteful if you don’t learn from it and apply some of the lessons as you forge your own path and improve.

Seeing this list for the first time, it reflects the tough year that was 2019. Health issues in the close family, year two of growing my business and lots of international and local travel. My go-to place when it’s tough is to slow down, focus on habits that are stable and I know are good for me and read to learn or relax.

I’m a binger, so I find I blast myself with a theme for a while until I’ve had enough then rotate through a few categories I like. Occasionally I throw in something I have no interest in to get out of the echo chamber of awesomeness ( my biased world view). I like self-improvement, science fiction, history, technology, experimentation and entrepreneurship / rapid growth.

Learning from those who have come before

On China — Henry Kissinger

Lesson: By far, one of the most impactful books I’ve read. The West plays win-lose Chess in fiscal quarters. China plays the 1000 year game like water flowing around pebbles, realising there is no absolute win-lose, just a sometimes uncomfortable compromise to live with and tolerate your neighbours, no matter how different.

Watching global maneuvering between the ‘West’ and China, it seems like there is so little effort expended to understand China and how it thinks and operates. Henry Kissinger gives a balanced view and great personal insight over many decades into the massive cultural differences. Politics is like Mars negotiating with Earth right now. Bizarre to watch in real-time.

The Gathering Storm, 1948 (Winston S. Churchill The Second World War Book — Winston Churchill

Who better to tell the story of WW2 than Winston Churchill?
Lesson: It’s shocking how easily we could have prevented this horrific war with a longer-term view, and by simply honouring international agreements from WW1 while not focusing on petty internal politics. Sound familiar?

The Virtues of War: A Novel of Alexander the Great — Steven Pressfield

The master of history-action writing, Steven Pressfield. History told as a novel.

Upskilling

Never Split the Difference: Negotiating As If Your Life Depended On It — Chris Voss

Lesson: 50/50 sucks. How to get what both parties want to set up the project for success.

Getting Things Done: The Art of Stress-Free Productivity — David Allen

Lesson: I re-read this annually to reset and remove complexity in my work processes, flow and prioritisation.

Every Tool’s a Hammer: Life Is What You Make It — Adam Savage

Lesson: Creation is iteration and that we need to give ourselves the room to try things that might not work in the pursuit of something that will.

Experimentation and Rapid Growth

Super Pumped: The Battle for Uber — Mike Isaac

Lesson: Starting a business is hard. Rapid growth is harder. Changing an industry requires a touch of madness.

Loonshots: How to Nurture the Crazy Ideas That Win Wars, Cure Diseases, and Transform Industries — Safi Bahcall

Lesson: Rethink of ‘disruptive innovation’ and more focus on the incremental change of Strategy vs Product innovation with a focus on how to create teams for loonshot vs franchise business.

A loonshot refers to an idea or project that most scientific or business leaders think won’t work, or if it does, it won’t matter (it won’t make money). It challenges conventional wisdom. Whether a change is “disruptive” or not, on the other hand, refers to the effects of an invention on a market.

Turning the Flywheel: A Monograph to Accompany Good to Great — Jim Collins

Lesson: Focus on my flywheel for 2020

The Right It: Why So Many Ideas Fail and How to Make Sure Yours Succeed — Alberto Savoia

Lesson: Many lessons on how to beat the beast of failure here, but working with Alberto Savoia to build my business, Exponentially, has been a privilege and opened the door to working with hundreds of smart people thinking about how to spend time building the right it!

Secrets of Sand Hill Road: Venture Capital and How to Get It — Scott Kupor and Eric Ries

Lesson: I was gifted this at a visit to Andreessen Horowitz in July. “It’s not about the money. It’s about the F-ing money.”

Great by Choice: Uncertainty, Chaos, and Luck — Why Some Thrive Despite Them All (Good to Great Book 5) — Jim Collins

Lesson: “Greatness is not a function of circumstance. Greatness is largely a matter of conscious choice and discipline”.

What You Do Is Who You Are: How to Create Your Business Culture — Ben Horowitz and Henry Louis Gates

Lesson: (1)The best idea should always win, and (2) virtues (what we do and how we act when nobody is looking) always trumps values (written down nonsense nobody does or remembers).

Trillion Dollar Coach: The Leadership Playbook of Silicon Valley’s Bill Campbell — Eric Schmidt, Jonathan Rosenberg, and Alan Eagle

Lesson: Cut the BS and enable your teams to be excellent.

Awaken the Giant Within — Anthony Robbins

Lesson: I was biased towards listening to Anthony Robbins. I thought it’s cheesy nonsense, but there’s a lot of wisdom in radical; self-enquiry and asking the hard questions of myself. And realising how few answers I really have.

Do Better Work: Finding Clarity, Camaraderie, and Progress in Work and Life — Max Yoder

Lesson: Focus on mutual opportunities for benefit.

Self-improvement

Stillness Is the Key — Ryan Holiday

Lesson: Limit your inputs to what is useful and supports what you’re trying to achieve in your life.

Why We Sleep: Unlocking the Power of Sleep and Dreams — Matthew Walker, PhD

Lesson: Why did I wait so long to learn about my body and how it really functions? I’ve slept an average of 8 hours a night for the past 10 years, so I’m on the right track. Now I understand why it matters so much.

Everything Is F*cked: A Book About Hope (The Subtle Art of Not Giving a F*ck (2 Book Series)) — Mark Manson

Lesson: There’s no point to this whole living exercise, so enjoy your brief time here. Summed up best here:

To transcend the transactional realm of hope, one must act unconditionally. You must love someone without expecting anything in return; otherwise it’s not truly love. You must respect someone without expecting anything in return; otherwise you don’t truly respect him. You must speak honestly without expecting a pat on the back or a high-five or a gold star next to your name; otherwise you aren’t truly being honest.

The Meaning of Life — The School of Life

Lesson: I read this while my brother was fighting cancer and it really focused me on what’s important. The right book at the right time.

On the Brink of Everything: Grace, Gravity, and Getting Old — Parker J. Palmer

Lesson: At 52, it’s worth understanding how smarter people deal with each new decade or life-phase. My life now is more about being fulfilled than owning shiny things. And trying to avoid this:

“Most of us,” as Merton brilliantly observed, “live lives of self-impersonation.”

Digital Minimalism: Choosing a Focused Life in a Noisy World — Cal Newport

Lesson: Tech isn’t evil, but you need to consciously choose the least amount of technology to do the job that needs doing. You can’t rely on willpower because you’re competing with armies of the smartest, best-paid people on the planet designing experiences to keep you clicking, swiping and browsing.

What makes general-purpose computing powerful is that you don’t need separate devices for separate uses, not that it allows you to do multiple things at the same time.

How to Sit (Mindfulness Essentials Book 1) — Thich Nhat Hanh and Jason DeAntonis

Lesson: Mindfulness has been my number one hack for the last three years. In this turbulent year, mindfulness has helped me ‘settle’ during periods of high stress.

The Manual: A Philosopher’s Guide to Life (Stoic Philosophy Book 1) — Epictetus, Ancient Renewal, and Sam Torode

Lesson: Whenever distress or displeasure arises in your mind, remind yourself, “This is only my interpretation, not reality itself.”

“If you wish to improve,” Epictetus once said, “be content to appear clueless or stupid in extraneous matters.”

Reboot: Leadership and the Art of Growing Up — Jerry Colonna

Lesson: Confronting truth bombs end to end. “How are you complicit in creating the conditions of your lives that you say you don’t want?”

The Laws of Lifetime Growth: Always Make Your Future Bigger Than Your Past — Dan Sullivan and Catherine Nomura

Lesson: It’s ok to have a 25-year plan. I love that Dan Sullivan, at 70-something years old, has a 25-year plan. Also comforting to think about my goals over 1 5 or ten year period. Makes it much more achievable. A simple example is: If you want to make 1 Million dollars, it’s almost impossible to do this year, but it’s only 100k a year if you do it over 10.

Escapism

36 Righteous Men: A Novel — Steven Pressfield

Strange book but a fun read.

The Time Travel Chronicles (Future Chronicles Book 7) —

Samuel Peralta, Robert J. Sawyer, Rysa Walker, Lucas Bale, Anthony Vicino, Ernie Lindsey, Carol Davis, Stefan Bolz, Ann Christy, Tracy Banghart, Michael Holden, Daniel Arthur Smith, Ernie Luis, Erik Wecks, and Crystal Watanabe

The A.I. Chronicles (Future Chronicles Book 2) —

Samuel Peralta, David Simpson, Julie Czerneda, Chrystalla Thoma, Pavarti K. Tyler, Susan Kaye Quinn, Peter Cawdron, Angela Cavanaugh, E. E. Giorgi, Alex Albrinck, Sam Best, A.K. Meek, Patrice Fitzgerald, Logan Thomas Snyder, and Ellen Campbell

The End Has Come (The Apocalypse Triptych Book 3) —

John Joseph Adams , Hugh Howey , Seanan McGuire , Jonathan Maberry , Scott Sigler (Author), Ben H. Winters , Carrie Vaughn , Jamie Ford , Elizabeth Bear (Author), Ken Liu

The End is Nigh (Apocalypse Triptych Book 1) —

John Joseph Adams , Hugh Howey , Jamie Ford , Paolo Bacigalupi , Seanan McGuire (Author), Sarah Langan , Nancy Kress , Jonathan Maberry , Tananarive Due , Scott Sigler , Charlie Jane Anders

Wastelands: The New Apocalypse — John Joseph Adams

Good mix of short sci-fi stories to discover new authors.

Change Agent — Daniel Saurez

Daniel Saurez always writes excellent action sci-fi.

My Takeaways

• Stay focused on a healthy body, spirit and mind. The body is the engine that fuels the mind and spirit is relationships that bring the feeling of fulfilment.

• Keep learning

• Keep working hard with purpose

• Don’t succumb to ‘rugged individualism’. Find the multiplier.

• Avoid busyness. It’s ok to do nothing sometimes. It creates space to think.

• Play more. Life doesn’t have to be so serious all the time!

If I zoom out, It’s been a privilege to learn from all these smart people that took the time to capture their thinking and pass on their wisdom. Bring on 2020!

Speed in innovation is vital for results; it enables companies to focus quickly on emerging consumer trends and can drive costs down and quality up.

Research shows that overly long development periods remain one of the biggest obstacles in innovation. One study from BCG cites this as the most problematic issue of 6 significant hurdles in the innovation process.

Increasing speed to market will boost a company’s top and bottom lines and the financial benefits will usually outweigh the up-front costs of pushing speed to market. Pretotyping can reduce those up-front costs and save months in development.

How can Pretotyping help speed things up?

From an innovation standpoint, there’s more than one aspect to speed… there’s the rate at which new products or services can be developed, in addition to the delivery speed of those products or services to the market…how fast can we get them on the table?

Some organisations will lean more heavily towards development in the first instance, while others will lean towards delivery. Whichever you sway towards, both styles of innovation will have some habits in common…most notably lean processes and prototyping.

It’s here that Pretotyping can really push the process into the fast lane. Pretotyping removes the need for wasted time spent developing the wrong idea. It hones and perfects the idea, asking the right questions at the right times as the Pretotyping process is followed.

The difference between Pretotyping and prototyping

A prototype can take a long time to build; months and even years in some unfortunate cases…and that’s far too long. A Pretotype can be built or conceptualised in a few hours and tested over a few days.

A prototype is trying to answer the question “Can we build or make this?”

A Pretotype asks “Should we do this?”

One of the techniques of Pretotyping includes reducing the process to the most basic elements of a new product or service. This is known as “The Pinocchio” because it’s a fake, a dummy…nothing more than a partial mock-up of the new product or service. It helps speed up the innovation process by allowing creators to decide on features early on, to test or collect feedback and usage data and to analyse that data.

This technique was famously used during the creation of the Palm Pilot…the first incarnation of which was a block of wood with sketched-on buttons and a chopstick for a stylus. Although Pretotyping as a term was not known during this time, it was a concept that worked well enough for Jeff Hawkins to learn all he needed about the viability of the product before he launched into building a prototype.

Alberto Savoia, the Godfather of Pretotyping who developed the initial concept of Pretotyping while working as Google’s Innovation Agitator, defines Pretotyping as “building the right product before you invest in building your product right.”

Pretotyping enables innovators to use imaginary scenarios, gain feedback from the right audience and learn more about the practical use of their idea before wasting precious hours building what could potentially be the wrong product.

The time spent researching a product or service which turns out to be unpopular in trials or which just happens to be a dud in performance can be saved very early on in the game via Pretotyping.

Today’s companies are no longer asking themselves if they need to consider speed in their innovation processes but rather how soon can they speed things up and how fast can they go.

Learn more about how Pretotyping can help your business succeed in innovation and gain traction through our consulting and workshops.

I’ve been using the Sony WH-1000 MX3 headphones since January. After many long haul and local flights, I started wondering if there are lighter headphones out there. I love them, but I started getting a slightly sore neck after a few hours.

After doing some research, it seemed the closest competition is the BOSE QC 35 II. According to multiple reviews, ANC (noise cancelling) and functionality are similar, but the BOSE is 1 ounce lighter and more comfortable. Today I tried them on a flight to Sydney (1.5-hour flight) and wow — was I surprised.

The Sony’s are in a completely different league! The noise-cancelling on the BOSE is ok at best, but aeroplane noise, announcements and fellow passengers chatting come through loud and clear, relative to the Sony. I also noticed the compression and decompression in my ears as we flew and was surprised by how good the Sony’s are in comparison. The BOSE are more comfortable, but marginally so. Not enough to swing me over to BOSE.

The Sony’s are a 10/10 for ANC vs around a 6 out of 10 for the BOSE. I now also appreciate the ear pressure control of the SONY. Super comfortable and better quality all round.

The weak point of the Sony is for making and receiving calls. The outbound call quality is inferior. The Bose wins hands down here.

My verdict: I’m sticking with the Sony.

The reason: Sound and noise-cancelling is next level and the reason for buying these headphones in the first place.

Innovation is a crucial component in the ongoing success of any business. A PwC survey reveals that 97% of CEOs agree that innovation is a top priority but no fewer than 94% of them are unhappy with their current innovation programs.

This naturally leads to the assumption that something must be very wrong in the world of innovation.

That’s a problem to be solved and problems are what begets innovation in its finest forms.

Enter Pretotyping

What is Pretotyping and how can it help solve the issue which the vast majority of CEO’s are experiencing in relation to innovation? What can Pretotyping add to the innovator’s toolkit?

At its heart, Pretotyping is comprised of a set of tools, techniques and tactics which are designed to help validate new ideas for new products quickly and accurately.

The ultimate goal of Pretotyping is to cut to the chase…to avoid time-wasting and ensure that you’re exploring and planning the right idea before you execute the wrong one and fail.

What does that mean? How can Pretotyping improve innovation processes and how can one know what the right idea is before it’s been tried and tested?

The strategies

The strategies as laid out by Alberto Savoia in The Right It have been designed to improve the process of innovation and maximise the chances of success.

1. Obey the Law of Market Failure.

2. Make sure you are building The Right It.

3. Don’t get lost in Thoughtland.

4. Trust only in Your Own Data (YODA).

5. Pretotype It.

6. Say it with numbers.

7. Think global, test local.

Looking at Pretotyping as part of the corporate innovators’ toolkit, what can be gained from the first few on this list?

Obeying the law of market failure: This makes pretty grim reading at first…the law of market failure is as follows. “Most new ideas will fail in the market, even if competently executed.”

Doesn’t sound very hopeful for most people does it? But it’s true…even the most successful enterprises regularly launch new products which end up dead in the water.

Take Google’s Mr Jingles…have you even heard of that? Whether you have or not, it’s one of a long list of Google’s failed products, launched in 2015 and scheduled to end in 2019.

If Google don’t always get it right, there’s no shame in accepting that failure is part of the business of innovation…but we have to ask why. Why do most new businesses or innovations fail? There are 3 main reasons.

· Marketing failure

· Poor product

· Poor premise

The last reason, poor premise is the most common reason for failure. The product is not relevant, the audience doesn’t care for it…it’s not The Right It.

The Right It: What is The Right It and how can we be certain we’re building The Right It? If we assume that most innovators know what they’re doing when they begin developing ideas, then we can also assume that they’re building something that works.

So if we’re confident that it works, then what makes something the Right It or the Wrong It?

The Right It is defined as “An idea that, if competently executed will succeed in the right market.” The Wrong It is, “An idea that, even if competently executed will fail in the market.”

Examples of the Wrong It are to be found in every industry. Ideas which seemed to offer all that was needed for success but which failed for their own reasons. Either the market wasn’t ready for it, people didn’t like it or there was no real need for it. The Wrong It will fail 100% no matter how well executed.

So how can corporate innovators use this information to know for certain if they’re pursuing The Right It?

Don’t get lost in Thoughtland

Thoughtland is that grey area of innovation where all that’s on offer are opinions and thoughts…or ideas. It’s a nice place to hang out in many ways. You can dream big, get your ego massaged by those who are in agreement with your concepts and when you come up with a great idea on paper, the instinct is to discuss, to share and garner opinion. That’s part and parcel of innovation right?

To a point.

When it comes to working out if a product is viable…if it’s The Right It, then opinions are not helpful in the slightest.

The problem with opinion

Opinion is just that. It’s subjective, biased, variable and changeable; it’s worth nothing in terms of usable data.

It’s the same with using research from other people’s projects…or OPD (other people’s data)…completely useless. OPD is data collected by other people, for other projects, at other times in other places and with other techniques. It’s dangerous. You may see a similar idea to your own which has failed but you can’t trust that data…because it’s not your own data or YODA.

What is YODA? It’s data which you have collected yourself, for your own idea and first-hand and with that data comes something called ‘skin in the game’. Skin in the game represents what you’re risking…your time, money, reputation.

To work out if an idea is viable, you need more than your own skin in the game. More than your team’s skin in the game. You need investment in the form of trust…you need other parties to put something at risk because they have faith in that idea.

If you can sell it before it’s been made…then it’s going to work. It’s the Right It.

How does that happen? How can anyone sell an idea before it’s been fully developed into an actual product?

Exponentially provides all of the answers to that question and more.

The tools, techniques and tactics needed to ensure your corporate innovation program pushes through to the next level are all part of what we offer.

Discover more about Pretotyping and the tools and strategies which it introduces; contact us and learn more about our workshops and consulting.

I wish more companies would stop the theatre of service,

• cut through their rigid, unhelpful process and

• not implement their internal perception of what they think good service is

and solve the customer problem fast.

The dreaded chat support popup

Yesterday I had an issue creating a complex automation in Pipedrive and pinged the chat window expecting the following:

Hi, I need help with xxxx

(Agent) hi!

Hi

(Agent) hi can we start with your name?

Me 🤔: ‘you know who I am. I typed it in when I started the chat and besides, I’m in your chat window using your service and I’ve authenticated by logging myself in’

….

(Agent) what can I help you with today 😀😀

Me 🤔 : READ.THE.CHAT.SUBJECT.YOU.ASKED.ME.WHEN.I.OPENED.THE.WINDOW!!

….

(Agent) here’s 3 links to a few 500 word articles. Go hunt for the answer yourself again.

Me 🤔: AAAAAARRRGGGH

(Agent) anything else I can help you with today? Remember to rate me 😊😘😍

Me 🤔 :

Fifteen minutes of my life wasted, and I hate this company that I used to love.

This is what great looks like — enter Pipedrive support

1. Open chat window

2. Type in my request for help

3. Agent greets me by name, has my account open and confirms my question with a proposed solution immediately.

4. Agent asks me to hold on for 2 minutes while she records a short personalised video showing me how to solve my specific request.

And done!

That’s 6 star customer support. Nothing fancy, no endless back and forth, just solve the problem and get me back to work.

This says to me as the customer that the company respects my time. They want to solve my problem. The agents are empowered to fix my issue the best way possible, without it being overcomplicated and rigid.

This results in an increase in my loyalty and more importantly in these days of fake, theatre driven everything — increased trust in the brand.

How do you serve your customers online?

If you see the online channel as a way to reduce call-centre headcount and get customers to do your work for you, you’re doing it wrong. Customers have no loyalty for a reason. It’s a two-way relationship like most quality relationships in life and built on trust.

Treat your customers with respect across all channels and they will stick with you.

Well done Pipedrive and thank you.

Anki Vector Robot and Magic Leap are two exponential technologies that have surprised me recently.

Magic Leap

The $2.3 billion startup that has taken four years to get its first product out the door has blown me away. I’m on the board of an Extended Reality startup, Phoria, so have seen multiple iterations of these technologies, from Google Glass through Oculus, Microsoft Hololens to the gold standard of VR, the HTC Vive. They’re all incredible tech, and useful in industry verticals like Real Estate, Training, Design Engineering, etc. but fail to answer the consumer question compellingly:

”What is it for? What can it do 10X better than I can do right now?” 
Without solving this, behaviour does not change.

Then they launched the Magic Leap on 8/8/18. Based on reviews by journalists who tried the Magic Leap, I expected a slightly larger viewport Microsoft Hololens.

I was so wrong.

Image, if you will, a computer slightly bigger than a mobile phone clipped to your belt and a light, comfortable headset. And a small mouse-sized controller. That’s it.

No cables, no pc, no phone.

Absolute freedom. Touching and engaging with the AR rendered world using your hands. Mapping a large room in real-time. This is the future. We have LEAPt across the chasm.

ANKI Vector

I love the idea of robots being useful and how frustratingly challenging this is to get right. I bought the HEXA, as 6-legged, Programmable, Highly Maneuverable Robot a few months ago and, although technically smart, it’s basically a radio control car with six legs. Sure, it’s programmable, but the community is tiny, and the sensors are few. Disappointed.

Enter Vector. “a robot sidekick for your home”.

They nailed it. This little guy roams around the desk, recognises you, gets excited when you’re around, throws tantrums, is not 100% controllable and has heaps of personality — just the right amount of sensors and awareness and randomness. I love the evolution of this tech. ANKI has created a crowdsourced platform of thousands of robots to learn from and the same number of humans to practice on. CEO and co-founder of Anki, Boris Sofman sums it up here on this a16z Podcast.

Anki Vector Meets Magic Leap

What happens when you put a smart little robot in an Augmented Reality world generated by Magic Leap?

Magic Happens

Anki Vector Robot meets Magic Leap Extended Reality

and this is what it looks like in the current / “real” world

My Predictions:

1. Magic Leap has started the exponential curve of mass adoption of useful, unobtrusive Extended Reality. ETA 2020

2. Vector has started the exponential curve of mass adoption for a smart, helpful robot. ETA 2022

Links

ANKI Vector: https://www.anki.com/en-us/vector
Magic Leap: https://www.magicleap.com/

Phoria XR: https://www.phoria.com.au/projects/google-io
Exponential Innovation: https://exponentiali.com

It’s year four of my experiment to figure out how to apply startup and scale-up techniques, tools, and tactics to corporate innovation.

After selling GetViable in 2013, a platform to help founders get from idea to MVP, I wanted to solve a bigger, seemingly obvious problem. How do you connect start-ups to corporate innovators to drive value for both?

Since July 2014 I’ve been running a multi-year experiment, to understand how to plug start-ups into corporates. Start-ups have ideas, entrepreneurial people and freedom of thought and corporates have money, scale, resources, mature processes, and customers.

My thesis is that you can use well-proven techniques, tactics, and tools used by start-ups and scale-ups in a corporate innovation environment to drive real innovation that delivers results.

What are great innovation results anyway?

• An employee engagement program to help staff think about problems in a new way, amplifying the work of the frustrated innovators in the business.

• A training program to teach these techniques to staff, like Lean Startup, Design Thinking, Pretotyping and Pirate Metrics so they have the tools to stop and assess ideas before wasting precious resources on the wrong ideas.

• An experimentation program to rapidly test, learn and prepare for new technologies, services or business models.

• An evangelist to help the organization to understand that the sky is falling right now and we better get off our asses and innovate.

Or the holy grail.

• Creating disruptive, non-organic growth by finding that 10x breakthrough product that customers love and will part with cash to have.

All I needed was a company willing to let me figure it out.

Three years later I’ve worked for two of these companies.

Experiment 1: Outside-in. Consulting with ThoughtWorks

ThoughtWorks is on the edge of self-managed, empowered people/culture. They have a reputation for excellent, smart technical people, are niche and expensive and attract clients that want this. Perfect.

ThoughtWorks attracted this client-base and sent me in whenever someone said ‘disruption’, ‘innovation’, ‘startup’, ‘accelerator’, ‘fail-fast’, ‘lean startup’, etc. 
This allowed me to engage with forward-thinking members of large corporates who wanted to learn more and experiment.
Finding the brave soul driving innovation at these companies is key.

This gave me a good level of insight of what Tier 1 companies in Australia and New Zealand think innovation is, how they approach innovation and the challenges and opportunities executing innovation projects.

What I learned here is:

• Innovation creates strategic advantage. Most clients are happy for short-term engagements but realise very quickly that they need to execute their innovation initiatives themselves for exactly this reason. The challenge is they don’t have the right people, mindset or tools and techniques to do so in most cases.

• There is an abundance of smart people and great ideas inside each business. They just need to be unleashed and appropriately guided and managed. Finding ideas is not the problem — figuring out which ideas to pursue or discard is the challenge. Pretotyping is ideal for this.

The opposite, however, is true.

• Sticking ideas onto a wall, chatting about them, Lean Startup, Lean Canvas, Pretotyping, etc. seem simple on the surface. Few people put in the effort to understand and execute these correctly or to learn the right way to approach early stage innovation, resulting in poor outcomes, money and time wasted on the wrong ideas and as a result, surprise — poor or no outcomes.

Experiment 1 Complete. It was time to move on.

Experiment 2: Inside-out. Heading Innovation at Sportsbet

I was looking for a high growth, digital e-commerce company that genuinely wanted to experiment and innovate. The company also had to be relatively autonomous with decision making — hard to find in Australia as most larger corporates are sales offices of larger conglomerates, regardless of what they tell you. I wanted to have a platform to figure out what worked, test these techniques at scale and plug early stage start-ups into the process to innovate at pace.

Sportsbet fit the bill perfectly for this phase of the experiment. Sportsbet gave me a decent budget and leeway to mold the team in the best way we could. We settled on three startup techniques to filter out the good ideas from the not-yet-ready ideas:

• Pretotyping by Alberto Savoia from Google / Stanford

• Lean Canvas by Ash Maurya

• 500 Startups Pirate Metrics

We tested hundreds of ideas by combining these three approaches, saving millions of dollars by not building the wrong stuff. Quickly validating ideas to productise them and creating an environment where everyone could participate in innovation.

What I learned here

One the biggest learnings is that innovation is a new discipline for most and tough to execute.

As an Innovation Leader:

• You’re a change agent. And everybody hates change.

• You’re an evangelist.

• You’re a salesperson.

• You’re a technologist.

• You’re a VC.

• You’re a cynical optimist.

• You’re a storyteller.

• You’re a mentor.

• You’re a relentless communicator.

Outside again

At the end of July 2017, I left the Head of Innovation role at Sportsbet.

Every few years I like to step out, assess the landscape and deliberately choose where I focus my energy next. This is that time.

I think of employers as systems I pass through where we exchange value — I bring knowledge, capability, and outcomes and they bring knowledge, resources, customers, and cash. This relationship needs to be in balance, and when it’s not one of us should leave.
 
In both cases, I decided to leave while we still valued and liked each other. The business is in a good state to continue on the innovation path it has chosen, hopefully enhanced in some small way by me being there. My relationship with the people and business remain in place for future engagement.

After three years, I’ve learned that Innovation Leadership needs:

• Unwavering executive support. Test this with Question 1 from McKinsey’s ‘The eight essentials of innovation’,

Do you accept innovation-led growth as absolutely critical, and do you have cascaded targets that reflect this?

which concludes with

‘In our experience, though, CEOs are likely just going through the motions if they don’t use evaluations and remuneration to assess and recognise the contribution that all top managers make to innovation.’

• a three-year horizon at most. Why? This is the tenure of many CEO’s and they’re working for their near-term bonus unless…

• there is an environment of genuine constraint to get traction. Think energy retailers, general retailers under threat from Amazon, the music industry, etc

• an unwavering belief and trust that the ‘process’ will deliver tangible and intangible benefits to the business,

• strategic clarity and alignment,

• the right people. People that don’t fit properly, challenge the norm, have startup or innovation experience and Get Shit Done.

• space and time to experiment,

• a global network of relationships,

• humility,

• being a strong and active node in the local innovation network (see Brad Feld’s thinking).

Experiment 3: Outside-in?

I know it’s time to move on and find the next thing. Right now this looks like working with scale-ups, accelerators, engaging with corporate innovators, venture partnering or innovation consulting.

I want a broader perspective and success looks like this:

When I look back in a few years time I’ve helped to impact entrepreneurs, corporate innovators, and the innovation ecosystem positively, at scale.

As the next step I’ve just returned from spending time with some of the biggest thinkers I know — the Singularity University Global Summit in San Francisco. This conference made a tremendous impact on my thinking last year and this year didn’t disappoint.

More on that to come.

Onwards…