The Autonomous GTM, Handshake Deal Protocol, and How to Present to Investors
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Good morning
In today's edition, among other things:
The Autonomous GTM
The Handshake Deal Protocol
How to Present to Investors
How to Reindustrialize a Country?
Work Never Gets Finished When You Are Drowning
The Future of Software Development
Onwards!
The Autonomous GTM
The entire go-to-market playbook that's powered SaaS growth for the past decade is fundamentally broken. We're watching the collapse of human-coordination-as-a-business-model, and most GTM, sales and marketing are still hiring like it's 2019 (and some like it’s 2009).
The future of revenue generation isn't about scaling headcount ergo - more people = more sales —it's about building systems that make headcount irrelevant.
From Madrona:
What Is Autonomous GTM?
The term “autonomous GTM” is more than a buzzy upgrade to sales automation. It describes a re-architected approach to how companies generate, qualify, and close revenue — one that replaces reactive workflows with systems that can act on goals with minimal human intervention.
Instead of relying on workflows patched together with point tools and human glue, this model treats GTM as an intelligent system: one that ingests data, reasons about what matters, and acts to drive results — without waiting for human input at every step.
(…)
Three major forces are converging to make autonomous GTM not only possible, but urgent:
AI-native infrastructure is finally ready. The rise of large language models, vector databases, and real-time orchestration layers has unlocked the potential for decision-making systems that mimic human judgment — without the human latency.
Buyers have changed. Modern buyers self-educate, bounce across channels, and make decisions asynchronously. Traditional GTM systems weren’t designed to follow this path — and they’re breaking under the weight of complexity.
Signals are everywhere — and mostly noise. Teams are drowning in alerts, data, and dashboards. The real bottleneck isn’t information — it’s synthesis and action. Legacy CRMs, designed as databases of activity, can’t keep up.
These shifts are forcing GTM leaders to admit a hard truth: Teams are hiring more people to coordinate more systems that still produce less output per head. We’ve been scaling the wrong things. Headcount doesn’t equal efficiency. Manual processes don’t scale. And coordination is not the same as progress.
Let me translate that for you. The average sales rep spends 70-80% of their time on tasks that have nothing to do with selling. They're updating Salesforce. They're sitting in pipeline reviews, guessing at probabilities. They're manually enriching leads, scheduling follow-ups, and playing email tag with prospects who ghosted them three weeks ago.
We built entire industries around this inefficiency. RevOps teams that exist solely to manage the complexity. BDR armies are doing work that a well-configured webhook could handle. Sales enablement platforms teach reps how to use other sales enablement platforms.
What's actually happening is we've created a massive coordination tax that compounds with every new hire. Each additional person doesn't just add their salary—they add meetings, handoffs, miscommunications, and tools to manage the chaos they create.
Moving toward autonomous execution isn’t just about tool selection. It’s a shift in architecture — in how data, decision making, and execution come together. Founders and builders must shift from just stitching tools together to designing systems that produce outcomes.
The modern GTM stack doesn’t just manage activity — it drives decisions. Its foundation includes:
Unified data ingestion across product, marketing, and sales
AI reasoning layers that predict intent and suggest next-best actions
Autonomous orchestration of actions like email, routing, or deal escalation
Feedback loops that improve performance over time
Superhuman, a fantastic e-mail app discovered something that should terrify every GTM leader:
"88% of customers expect a reply within 60 minutes, and 60% define 'immediate' as 10 minutes or less."
Now ask yourself: what percentage of your leads get a response in under 10 minutes. Probably single digit %. Not because laziness—because they're drowning in manual processes and admin.
What these companies understand—and what the old guard doesn't—is that GTM is fundamentally an information processing problem. You have signals (form fills, website visits, email opens), you have context (company size, industry, behavior patterns), and you have actions (outreach, qualification, routing).
The traditional approach? Hire humans to connect these dots manually. The autonomous approach? Build systems that connect themselves.
The modern GTM stack doesn’t just manage activity — it drives decisions. Its foundation includes:
Unified data ingestion across product, marketing, and sales
AI reasoning layers that predict intent and suggest next-best actions
Autonomous orchestration of actions like email, routing, or deal escalation
Feedback loops that improve performance over time
What can you do about it to improve?
First, run an audit of wasted time. Have every person on your GTM team track their time for one week. Not what they're supposed to be doing—what they're actually doing. You'll be horrified by how much time goes to coordination, data entry, and "managing the process."
Second, pick one high-volume, low-judgment workflow and automate it completely. Not partially. Not with human oversight. Completely. Lead routing is usually the easiest win. Set up a system that captures, enriches, scores, routes, and responds to leads without any human touching it. Measure the results.
Third, change your hiring criteria immediately. Your next GTM hire should be technical. They should understand APIs, be comfortable with AI tools, and think in systems rather than processes. If they can't explain how they'd automate their own job, they're not the right fit for the future you're building.
And here’s the advice from Madrona:
hat shift includes:
Rethinking hiring: The next GTM hire might be a GTM engineer, not a BDR manager. Tomorrow’s GTM orgs won’t just hire fewer people. They’ll hire different ones: AI-native leaders who manage hybrid teams of humans and intelligent agents. The CRO is no longer just a sales strategist — they’re a systems architect, orchestrating both human reps and autonomous GTM agents
Measuring systems, not people: What percent of your pipeline moves autonomously? Traditional teams spend 20–30% of their time on revenue-driving work. Some companies are already seeing a 25-30% increase through intelligent automation, with a goal of hitting 70-80%.
Treating playbooks as software, not slides. Ask smart questions: If you removed a tool from the stack, would reps miss quota? If you added one, would they raise it? Use quota-based evaluations to cut bloat and drive real impact.
Start with a usage and systems maintenance: How much time do you or your team spend debugging, maintaining, improving, and fixing all those fancy tools you’ve connected? Be honest.
Leverage rep feedback before bringing in consultants. Your GTM team and your customers often have the most actionable insights — and they’re free.
Challenge teams: If you’re advocating for a new tool, are you also committing to raising your quota?
Valuing observability and iteration over linear process fidelity. Linear process adherence — the idea that a rep must follow a sequence to win — is giving way to closed-loop systems that observe, learn, and adapt. Playbooks are no longer PDFs. They’re live systems, embedded in your stack and updated dynamically. That requires observability — not to micromanage reps, but to optimize the system itself.
Systems instead of headcount.
The Handshake Deal Protocol
Every day, some founders disconnect after a video call with an investor, thinking they just raised $X00k. Three days later, radio silence. The investor who was "super excited" and "definitely in" has ghosted them/
Most "yes" meetings are actually "no" meetings in disguise. The entire funding ecosystem runs on ambiguity and FOMO—and founders are the ones getting screwed often.
Y Combinator just dropped a protocol to try to fix this mess.
The protocol defines an offer as an amount to be invested, plus a valuation or valuation cap (or no cap), plus an optional discount. Here are some example offers:
$100k at a $5M cap.
$100k uncapped.
$100k uncapped with a 10% discount.
According to the protocol, you have a handshake deal if and only if the following happens:
The investor says "I'm in."
The startup sends the investor an email or text message saying “Can you confirm you’re in for [offer]?” — spelling out the exact offer including the specific amount and terms.
The investor replies yes.
Unless and until this process is completed, there is no handshake deal. So it is in the interest of investors to complete the final step, because until they do the startup is under no obligation to take their money.
Audit Trail
Since both parties will usually have mobile devices from which they can send such messages, they should ordinarily do it in person as the final step of the agreement. They should each regard it as suspicious if the other is unwilling to.
At the very least this protocol will tell us who's at fault if we get a report of a handshake deal falling through. But it should do more than that. A definite protocol that leaves a trail will both prevent founders from misleading themselves, and discourage investors from misleading them.
I don't think the offer has to specify the documents to be used. In practice this is rarely an issue. People either use one of the standard documents (for small investments) or negotiate in good faith (for large ones). Market terms are well enough understood that it should be easy to see who's at fault if one party is making difficulties about the terms, and that's all we ask from this protocol.
Makes sense.
How to Present to Investors
Staying on the topic of investors and founders. Quick guide from Sequoia on how to present to investors:
In the same way, you need to convey the main reasons why an investor should love your business in the first 5 minutes. We found the best way to do that is to open with 3 slides:
1.What’s changed? Explain what’s the discontinuous shift, break-through, or innovation that opens the window to create a substantial new company.
2.What you do: A one-sentence explanation of what your company provides to capitalize on that big change. It still surprises me how often we can get 20 minutes into a meeting without a clear picture of exactly what a company does.
3.Fast facts: Lay out the key metrics for your business: when were you founded? How many employees? What stage of development / market traction? What are you looking to raise? This helps the investor put the rest of the presentation in context.
At this point, the first 5 minutes are almost up and there’s just time to run through an agenda slide, which covers all the usual ground (e.g., product, market size, team, etc).
From here, many entrepreneurs roll right on to tell the story in greater detail. But your 5 minutes are up, and we suggest you pause and check in with your listeners.
And some pitfalls to avoid:
Pain: Be very clear about the problem you are solving. For consumer concepts, talk about user needs; for enterprise ideas, show a detailed understanding of your customer’s pain. If you cannot convince an investor there’s something broke, they will not be interested in a solution.
Solution: It’s not possible every time (e.g. for infrastructure software), but whenever you can, a demo is worth a thousand words. Failing that, screenshots and the workflow to bring the solution alive.
Market size: If it’s a new market, the best way to tackle this is to explain how many users or customers there are for the product/service, how this number grows over time, and how much each of these users/customers is worth (this last part is a chance to cover pricing/revenue model). If it’s a replacement market, for example where software is automating an existing service, then explain how big the existing market is today and how much you expect your solution to shrink it, through lower prices. One thing not to do is to put up huge numbers from some market study without any details behind them.
Competition: Better to identify all the competitors than have the investors discover them afterwards. That way, you can proactively explain how you are different.
Team: By this point, if the investor is interested, they will want to know about the team, so it’s worth spending a couple of minutes on the founders’ backgrounds, highlighting any special talents or experiences that make them well-suited to building the business.
Financials: It’s easy to lose yourself in the numbers. We suggest keeping it simple and just showing on a timeline how you would spend the money (e.g., headcount) to achieve specific milestones (e.g., launching the service).
How to Reindustrialize a Country?
Fascinating presentation from Chris Power from Hadrian. It unpacks so many things on reindustrializing the US, what we should do in Europe too, and how that compares to China.
Just to raise your curiosity:
Full video here:
Work Never Gets Finished When You Are Drowning
From Brando Olson via Kpax:
SIMILAR TO MY FAVORITE WHITE-WATER river, organizations experience various states of flow and flood.
When an organization is flowing like it should, things just seem to work right—people work hard, actually deliver great things with ease, and love their work. Innovative ideas emerge and transform into real value. Collaboration feels like second nature, and accomplishments pile up.
But in a state of flood, the work is too fast, too much, and most things take longer to finish than anyone expects. There is no limit to the amount of work that gets started, and an unlimited amount never gets finished. Flooding in organizations is what makes people feel like they’re caught in a wild frenzy of activity, overwhelmed, barely in control, and not getting enough work done.
Simply put, flood is the feeling of working hard while drowning in hard work.
It probably won’t surprise you to learn that most organizations are flooding. Some are aware of it, but most become oblivious to it because a raging river feels like it’s moving fast. The water may be moving fast, but you are moving slow.
Fast water does not mean fast travel. Chaos can be easily mistaken for the feeling of productivity when we are in a constant state of urgency. This happens especially when our entire culture of modern management—a term that encompasses the organizational management practices of our time that are extremely common but out of sync with reality—reinforces the illusion that working hard equals being productive.
In other words, it doesn’t matter how great of a paddler I am. If I’m swept up in a flooded river, I’m going to spend more time managing its mayhem and hurdles and less time moving toward my destination.
But there are even bigger tolls that a flooding river creates beyond productivity issues. In flooding organizations, leaders put people in positions where they are forced to choose between doing great work and prioritizing their own well-being. And in addition to the very real human cost, flooding organizations waste time and energy managing the flood instead of doing the actual work that matters most.
The Future of Software Development
Worth watching if you want to understand where we are going for software development:
Interesting Analysis and Trends
AI, Agents & Context Engineering
You’re Not Ready for AI Hacker Agents LINK
When Agents Attack: How AI Collapses Workflows LINK
Nobody Knows How to Build With AI LINK
LLM Seeding LINK
AI Agents & PMs LINK
Vibe Coding Needs Context Engineering LINK
Context Engineering (Felicis) LINK
Context Engineering (Blog) LINK
Hidden Technical Debt in AI LINK
Venture Capital, Founders & Markets
Peter Inge on Why You Shouldn’t Start a Company to Make Money LINK
How Founders Should Think About Pre-PMF Burn Rate LINK
Fund Size Is Strategy: Power Laws in VC LINK
Show Me the Money: Founders & Loyalty LINK
The Taxi Cab Theory of Venture Capital LINK
5 Charts Explain Crypto LINK
Books We’re Reading Summer 2025 LINK
Software for Hardware LINK
The Longevity Land Grab LINK
GTM, Marketing & Growth
40 Things We’ve Learned About Marketing LINK
Get Recommended by ChatGPT LINK
Search Patterns in 2025 LINK
The Substack AI Report LINK
AI + Industry (Health, Infra, Reindustrialization)
The AI & Healthcare Opportunity LINK
American Reindustrialization: Empty Promises vs Opportunity LINK
The Invisible Back Office for Field Teams LINK
Culture, Theory & Long-Term Thinking
The Hater’s GUI LINK
Philosopher/Builder Summer Reads 2025 LINK
In Defense of Self-Direction LINK
Very Bad Advice LINK
Consumer Manifesto LINK
Talent, Tools & Legal
AI for Recruiters in 2025: What Gets Automated, What Stays Human LINK
Startup Legal Document Pack LINK
P-Hacking in ML LINK
Insights for Enterprise AI Builders LINK
Research & Papers
Meditations
Seth Godin:
Uncomfortable facts are often the most helpful ones.
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Thank you for your time,
Bartek