I'm rooting for open source
1. Key Themes
Open Source AI as the Pro-Market, Pro-Innovation Position
Rechtman argues that open-source AI models — not proprietary oligopolies — are the correct structural outcome for innovation, competition, and American geopolitical interests.
"The most pro-social, pro-innovation, pro-market outcome is for model development and infrastructure to be a fiercely competitive commodity business not a (gross) margin rich oligopoly propped up by government mandates as quasi-GSEs."
Abundant, Free Intelligence Unlocks App-Layer Value Creation
The thesis is that cheap/open intelligence shifts value downstream to builders and consumers, not upstream to model creators.
"If intelligence is abundant and free, we can see a difference in kind — the most interesting AI businesses are predicated on some combination of model diversity, local models, free intelligence."
AI Industrial Policy as a National Competitiveness Risk
Rechtman draws a direct analogy between AI and energy policy, warning that protecting closed American labs could mirror America's costly bet on oil over electrification.
"The worst case scenario of a ban on open source (chinese) models is that LLMs/intelligence winds up like energy. As the rest of the world moves to the electric stack and lithium ion supply chain, America doubles down on oil, losing an opportunity for global leadership to enrich regime-proximate-toadies."
Vibe-Coded Custom Tooling as a New Cost Structure for Operators
Rechtman personally replaced a $10,000/year SaaS CRM with a custom-built tool for ~$2,000 using AI-assisted development, signaling a structural shift in build-vs-buy calculus.
"I spent the last week and ≈$2k building a pretty slick replacement for a $10k SaaS product with Fable while consolidating together a bunch of vibe coded side projects that I'd built to supplement the SaaS we're now churning from."
Talent Gap: "Slop Cannons" as an Emerging High-Demand Hire
A new archetype of worker — high tool-use generalists — is in demand but lacks a dedicated recruiting infrastructure.
"There is a real/seeming dearth of recruiting firms focused on non-technical hires, especially slop cannons (high tool use generalists) — or at least I don't really know them. I've had multiple companies ask me for help in finding these people."
2. Contrarian Perspectives
Most VCs Are Wrong to Oppose Open Source AI
Rechtman argues that large VCs reflexively oppose open models not on principle, but because they follow power — siding with incumbent foundation model labs and current political winds.
"Lots of the biggest VCs will reflexively be open models them because 1) Trump is against them 2) the American foundation model labs are against them — most investors reflexively kowtow to the powerful/root and side with winners."
This is a direct challenge to the consensus VC position and implies a mispricing: if the open-source ecosystem wins, the investors currently aligned with closed labs will have backed the wrong structural outcome.
Open Models Are Only "Decelerationist" Because Incumbent Labs Need Them to Be
The common argument that open-sourcing AI slows R&D investment is reframed as a self-serving narrative by labs that have capitalized themselves on oligopoly assumptions.
"Open models are only decelerationist (discouraging investment and recursive improvement) insofar as the leading labs have structured/capitalized themselves on the basis of oligopoly and protectionism. A fiercely/maximally competitive market for intelligence is better than the captive world we're otherwise moving to."
State-Backed American AI Labs Would No Longer Be "American"
Rechtman makes a political-economy argument that government capture of AI labs is itself an un-American outcome — inverting the framing of "protecting American AI."
"If our labs become state backed and controlled they'll no longer really be 'American' in any meaningful sense — and neither will we."
3. Companies Identified
- Description: AI-assisted software development tool
- Why mentioned: Rechtman used it to build a custom CRM in roughly one week for ~$2,000, replacing a $10,000/year SaaS product
- Quote: "I spent the last week and ≈$2k building a pretty slick replacement for a $10k SaaS product with Fable."
- Description: AI content detection platform, now integrating with Substack
- Why mentioned: Highlighted as a case study for an emerging arms race dynamic in bot/AI detection; Rechtman half-seriously floats funding a company that builds self-improving detection-defeating agents to stress-test it
- Quote: "Pangram is integrating with Substack for AI detection. There's a great opportunity to create an 'AI safety and research lab' that builds self improving bot-detection-defeating-agents in order to protect us from bots which defeat bot detectors."
- Description: Startup that acquired the assets and customers of competitor Alden
- Why mentioned: Cited as an example of category consolidation — a winner emerging from a competitive field
- Quote: "Phoebe acquired Alden's assets and customers. This is what it looks like when a winner starts emerging in a category."
- Description: Early-stage venture fund (~$325M)
- Why mentioned: Author's firm; provides context for his investment perspective
- Quote: "I'm a partner at Slow Ventures, where I lead pre/seed rounds from a ≈$325M fund."
a16z (Andreessen Horowitz)
- Description: Major venture capital firm
- Why mentioned: Singled out as one of the few large VCs taking the correct position on open-source AI, against the broader consensus
- Quote: "To their credit, a16z seems to be saying the right thing here."
4. People Identified
- Description: Partner at Slow Ventures, pre/seed generalist investor
- Why mentioned: Author; shares personal operating experiments (custom CRM build) and investment thesis on open-source AI
- Quote: "I'm a generalist investor looking for weird takes on important stories: N-of-1 companies taking non-obvious approaches to markets that matter."
Nathan (last name not provided)
- Description: Builder/creator affiliated with Slow Ventures' community (attended Slop Con and "Slow")
- Why mentioned: Built a "crime simulator" as an example of "performative software" — a concept Rechtman finds worth watching
- Quote: "He's been interested in the idea of 'performative software'... software has finally been added to the list of mediums for us to use."
5. Operating Insights
Investor Updates Are Infrastructure, Not Marketing
Rechtman reframes investor updates as a discipline for the founder, not just a service to investors — and offers a tight framework for execution.
"Investor updates are a good way to measure for yourself if you're closing your books well, on top of your numbers, and hitting your plan... If it's really hard to get your numbers together that's a separate yellow blinking light which itself is worth reporting."
Tactical rules: Keep it short, send monthly, lead with numbers over narrative, be honest about messiness, and feel empowered to remove investors who create noise without value.
Custom-Built Tooling Can Dramatically Undercut SaaS Costs
The build-vs-buy equation has shifted materially. Founders and operators should audit their SaaS stack for tools where a tailored custom build — using AI-assisted development — could deliver more value at a fraction of the cost.
"I'm gonna end up saving a few shekels/year (savings TBD because there's now variable spend) [and] using a product much more tailored to what I actually need with flexibility to change it."
The caveat: this works for single-user or small-team contexts. Rechtman explicitly notes he "definitely wouldn't want to have to support multiple users or try to commercialize what I've done."
6. Overlooked Insights
The MCP Server as an Investor-Facing Interface
Rechtman mentions in passing that his newsletter content is accessible via an MCP (Model Context Protocol) server — meaning AI agents can query his prior writing and thinking directly.
"You (or your agents) can also read/chat with 99D via my MCP server."
This is a low-key but forward-looking move: making one's intellectual output machine-readable and agent-accessible as a distribution and relationship-building tool. It's a model worth watching for investors, operators, and knowledge workers building personal brands.
Consolidation Signal: Asset Acquisitions as Category Resolution
The Phoebe/Alden example is mentioned in a single bullet, but it points to a broader pattern worth tracking — distressed asset acquisitions as a leading indicator that a market is thinning to one or two survivors.
"Phoebe acquired Alden's assets and customers. This is what it looks like when a winner starts emerging in a category."
For investors monitoring crowded early-stage verticals, watching for these acqui-asset deals (as opposed to traditional M&A) may be an underutilized signal of category maturation.