Coding work is shifting from typing to directing AI
- Developers are using AI agents to write, test and review code, shifting their work toward directing automated teams.
- Software makers are reformatting documentation so agents can find and choose their tools.
- One startup CEO argues AI is most useful when it works alongside people, right where they work.
The coding shift is less about replacing a developer with one chatbot than turning software work into a process of directing and checking AI agents. That could change not only who writes code, but how developers choose tools and how software companies compete for their attention.
Theo Browne described T3 Code’s Orchestrator V2, which lets a lead agent launch sub-agents across different model providers to review work. The change arrived in a pull request that added 400,000 lines of code, according to the show’s discussion. Browne said his custom workflows make models debate proposed changes and reach agreement before filing or merging a GitHub pull request. The developer’s role, in this setup, is increasingly to set up the process and judge its results.
Nathaniel Whittemore, on The AI Daily Brief, described a related challenge for established software businesses: AI can help individuals recreate or build complex products. He highlighted game developers’ claims that models can handle tasks from game logic to sound, potentially letting small teams produce more ambitious work. These are forecasts, not proof that studios or commercial software are about to disappear.
The next contest may begin before an agent writes a line of code. On This Week in Startups, the team discussed devtool company Railway’s advice to publish documentation in clean Markdown and structured formats that AI agents can readily read. If developers increasingly ask agents to select and deploy infrastructure, clear documentation could help determine which vendor gets picked.
Superhuman CEO Shishir Mehrotra described a broader version of the same interface shift: AI that assists people at their cursor, inside the apps they already use, rather than only through a chatbot or a background agent. His company says its platform handles more than 125 billion language-model queries a week across 40 million daily users. The larger change is that software work may hinge less on typing every instruction by hand - and more on directing, checking and making tools legible to AI.
Source Intelligence
- Deep dive into what was said in the episodes
Flying Cars, OpenAI Spies, Why AI Isn’t Sticking (Superhuman CEO) • Oct 17
- Shashir Marotra distinguishes AI tools that assist alongside a user from chatbots and task-doing agents. Grammarly and Go serve about 40 million daily users across a million distinct surfaces per day, generating over 125 billion LLM queries weekly, or about 3,000 per user per day.
- Lon says the newsletter favors practical tactics over generic inspiration, including Whisperflow’s approach of closely coaching a small creator group rather than quickly scaling to 100 UGC creators. He also highlights Railway’s agent-discovery advice, such as publishing documentation in Markdown for agents to read.
Also discussed on this episode: (13)
Startups (2)
- Shashir Marotra says Superhuman acquired Rose, GPTZero, and Fathom since his previous appearance. Superhuman is integrating Rose’s spreadsheet product, keeping GPTZero relatively independent, and plans a more integrated Fathom notetaker.
- Sponsor claims included Plaud’s one-press recording and a 10% discount, Every’s startup formation and international contractor services, and PayPal’s repeat-use figure for Pay Later. Jason also promoted GoDaddy’s domain security, privacy, auction, and forwarding services.
Safety (4)
- Shashir Marotra says GPTZero checks authenticity across education, journalism, science, and recruiting, where users want evidence of authorship or understanding. Its live internet scan reported AI in 6% of Reddit and 13% of X.
- Shashir Marotra says AI detectors score in the high 90s on some benchmarks, though short writing is harder to assess; he says he generally trusts the detector when users dispute a score. He argues authors should disclose collaborators, including AI, and take responsibility for work published under their names.
- Prosecutors allege OpenAI engineer Abdul Raman Alphazan hid a recording device in an executive conference room, while the FBI arrested him and OpenAI reportedly trained staff to spot espionage approaches. Jason suspects financial or corporate intelligence gathering, not state efforts to obtain model secrets, but says the motive is unconfirmed.
- Eight states sued OpenAI, alleging ChatGPT lacks safeguards for children and vulnerable users and was marketed as safe for children under 13; the states seek repayment of money earned while minors were harmed and an end to deceptive safety claims. Jason argues AI companions are harmful, especially for children, and favors a gated kids’ tutor that guides rather than gives answers.
Enterprise (2)
- Shashir Marotra says Fathom’s notetaker will draw on Superhuman’s mail, calendar, and integrations to capture context before, during, and after meetings. He argues that teams speak about 90% of their work, leaving most of that information undocumented and unavailable for follow-up.
- Shashir Marotra says companies use Go to enforce style guides and compliance rules inside the apps where employees work, including restrictions on claims about stock prices. Jason wants administrator alerts when paid Grammarly accounts stop running; Marotra says team-wide standards are a common request.
Education (1)
- Jason says new hires often struggle to write and argues writing should be a basic job qualification. Shashir Marotra says university studies found Grammarly users improved grammar, and compares AI rules to calculator rules: define when tools are allowed, then assess core skills without them.
Models (1)
- Keith Pis describes modern lead enrichment as using web-search LLM providers such as Exa to scan large numbers of documents, find current information, and update a CRM. He contrasts this with older databases built through paid manual calls and record-keeping.
Media (1)
- Jason says the newsletter’s team vets roughly 25 candidate stories, then adds context and graphics so readers avoid hours of research; Lon uses AI to surface candidates but reviews and edits the work. The newsletter offers annual access for $250, with its first 100 subscribers offered $100 pricing.
Labor (1)
- Jason recommends posting separate junior, business-writer, and senior openings with fixed salary bands of $60,000, $75,000, and $90,000, rather than insisting on one experience level. He also warns employers to assess job-related communication ability, not accent or other protected traits, and to follow local hiring rules.
Autonomous Vehicles (1)
- Lon reports that Tesla demonstrated a driverless Roadster jumping and flipping with compressed-air propulsion, with 10 nozzles and a claimed 0-to-60 time under one second; production is planned for 2028. Jason says practical self-driving matters more to buyers than extreme acceleration and speculates Tesla and SpaceX could merge by year-end, citing online reports rather than inside information.

Nathaniel Whittemore
How the Latest AI Leap Is Disrupting Business Models • Oct 15
- Developer Brandon Thomas used Claude to decompile Photoshop and rebuild it through clean-room reconstruction, then generated incomplete copies of Adobe’s suite and offered them free against a $100-per-month product. Nathaniel Whittemore says Adobe shares opened down 3% after the story spread, while arguing that enterprise SaaS customers often pay for maintenance and support, not software code alone.
- Game-engine developer George Kahl says Opus 5.5 can handle code, shaders, systems, level logic, sound, tools, and debugging well enough to move toward solo-made premium games; he estimates that individual developers could release their own visions in one to two years. Andrew Curran says models already produce stable game mashups in a day, while Alex Finn predicts a 2027 AI-game gold rush.
Also discussed on this episode: (14)
Startups (2)
- Financial Times reports Anthropic told investors it generated $16.8 billion in Q3 revenue, up 45% from Q2. The company said adjusted gross margin was 85%, adjusted operating margin 11%, and free cash flow positive; its adjusted figures exclude stock compensation, training costs, and revenue shares.
- Reuters reports Anthropic expects $110 billion in annual revenue by year-end, implying a 57% Q4 jump from its $70 billion Q3 annualized pace. Nathaniel Whittemore says the company is targeting a $2 trillion IPO valuation, and its public filings could omit Q3 results because statements may be 134 days old.
AI Infrastructure (1)
- CoreWeave’s 2032 unsecured bonds fell to 80 cents on the dollar and traded at a 15% yield as its shares dropped 15%, against a 1.6% Nasdaq decline. Analyst Gil Luria argues that borrowing at 9% to earn 5% destroys value; CEO Mike Intrator says the market misunderstands the company, while SEC filings show insiders selling shares.
Chips (1)
- ASML says chipmaking-tool demand exceeds its capacity for at least two years, despite a previously announced 30% delivery increase. CEO Christophe Fouquet says customers want more tools and some orders extend to 2029 and 2039; CFO Roger Dassen says adding major capacity by 2028 is extremely difficult.
Safety (2)
- Nvidia CEO Jensen Huang says he would consider stopping chip supplies to an irresponsible AI developer, but only after discussing the issue and within limits on policing customers’ use of general-purpose technology. Huang frames safety as an ongoing engineering task and announced $250 million in computing power for UK safety research over five years.
- Court documents say the Saudi national accused of planting a listening device at OpenAI booked a one-way flight for October 12. Prosecutors sought a sealed indictment and arrest warrant on October 8, and the suspect was arrested the next day; the case highlights how AI firms train new hires to spot insider threats and foreign intelligence approaches.
Banking (1)
- Bank of America hired 1,000 contractors to help 3,000 employees fix vulnerabilities identified by Mythos. CEO Brian Moynihan says the work, combined with anti-money-laundering requirements, added hundreds of millions of dollars in Q3 costs; Jamie Dimon says Mythos has increased banking cyber risk tenfold, prompting JPMorgan to focus on remediation.
Media (1)
- Reuters reports that a fake AI-generated bear image triggered a real animal-control response in a Russian village. After authorities found no bear, the woman who made the image was fined 15,000 rubles, about $178.
Coding (2)
- AI-assisted decompilation and game mashups are colliding with a struggling console business: console sales are at a 13-year low, studios have cut tens of thousands of jobs, and hackers are using AI to speed PS5 exploits. Bloomberg Intelligence argues streaming and data-center AI could weaken consoles; the PS5 base model now costs $650, up from $500 at launch, while the Steam Machine is priced at $1,000.
- Epic Games has banned handwritten code and shifted developers toward an AI-first production model, including AI-generated art, while delaying its Disney battle-royale shooter. CEO Tim Sweeney says AI should help teams create more and better; the company’s new vibe-coded launcher shipped with visible bugs despite faster launch times than Steam.
Big Tech (1)
- Xbox CEO Asha Sharma says decompiled games challenge assumptions about software, hardware, creation, and play. Xbox responded by forming Xbox Labs, a small internal team to develop and expand ideas enabled by AI; Sharma argues that broader access to games and letting players become creators can benefit players even when it unsettles existing business models.
VC (1)
- Ithaca Holdings, led by former Sequoia partner Ravi Gupta and former Meta executive John Hageman, announced a deal to take control of struggling Bumble. Gupta argues that accessible intelligence could make human connection more valuable and that a small, AI-focused team can rebuild a business; Bumble’s market capitalization peaked at $14 billion after its 2021 IPO before its share price fell 95% the following year.
Markets (1)
- Bending Spoons’ strategy is to acquire established brands with revenue, pool staff, and use AI to lower operating costs; its portfolio includes AOL, Vimeo, Meetup, Evernote, and Airtable. Berkshire Hathaway invested another $330 million in a private share placement after investing $600 million in the company’s July IPO, bringing Berkshire’s stake to 4% and helping lift the stock 40%.
Enterprise (1)
- David’s Bridal is expanding from wedding dresses into AI-powered planning through its “aisle to algorithm” strategy, using a vendor marketplace and customer data gathered from appointments, shopping, and services. President Olena Wilk says standard AI coding tools let a small team build what once took over 100 people; the company emerged from bankruptcy after filing in 2023.
OpenAI's Dev Day Was a Disappointment & T3 Code's New Orchestrator Shines • Oct 12
- Theo and Ben discussed merging T3 Code's Orchestrator V2 pull request, which added 400,000 lines of code after 13,000 intervening issues. The feature allows agents inside a thread to natively spawn sub-agents across various model providers like Soul and Gemini.
- Theo developed custom T3 Code skills named Soul Loop, Full Send, and Full Stop to automate multi-model verification. The workflow forces Opus and Soul to debate code changes until both models reach consensus before automatically filing or merging GitHub pull requests.
Also discussed on this episode: (8)
AI Infrastructure (3)
- Theo identified that Anthropic defaults to a one-hour cache duration for Claude Code subscriptions versus five minutes over standard APIs. However, recent system prompt changes in the Agent SDK broke cache reuse during thread compaction, forcing full token re-reads.
- Theo explained that historical model margins reached 98% when pricing was $10 per million input tokens and $125 per million output tokens. Margins compressed when labs cut output prices to $50 per million, forcing subscriptions to halve dollar-denominated usage caps.
- OpenAI's Ultra Fast mode provisions roughly six times the GPU allocation per request to eliminate latency for high-tier subscribers. Theo reported using $650 of API credit to review just two pull requests during early access testing.
VC (1)
- An Andreessen Horowitz consumer study revealed that only 2% of US households pay for AI services. Within paying users, the top 40% spend $27 monthly, the top 10% spend $150, and the top 1% spend $1,000 monthly, driving over half of total spend.
Models (1)
- OpenAI priced Soul 6.1 aggressively at $2 per million input tokens, $10 per million output tokens, and $0.10 for cache reads. Theo noted this 90% cache discount undercuts rival models, driving higher compute utilization and necessitating subscription rate limit reductions.
Open Source (1)
- Theo praised lightweight open-weight models like GLM 5.3 Flash and DeepSeek v4.1 Flash for staying focused on deterministic multi-step tasks. While incapable of high-level product decisions, GLM 5.3 Flash reliably audited 1,300 pull requests on T3 Code without failing.
Enterprise (1)
- Theo spends $4,000 monthly on AI subscriptions for his team at Ping Labs, with $2,500 dedicated to his personal inference. Ben pays for OpenAI's $500 monthly plan, highlighting how developer power users massively outspend typical consumer baselines.
Chips (1)
- Theo criticized Cerebras hardware for suffering noticeable model capability regressions compared to standard Nvidia GPU clusters. He noted Cerebras prioritizes direct enterprise compute deals, such as serving Jane Street, over refining developer dashboard experiences.

