Signal or Noise
We run through the week's AI headlines and make the call: is this actual signal worth paying attention to, or just noise clogging the timeline?
Real talk. Unpopular opinions. No hype. Two builders cut through the AI hype cycle every week — and call it like it is.
Hosted by Oscar Gallo & Matt Wozniak
EP 23 · September 15, 2026 · 71 min
In machine learning, “human in the loop” means a human who provides oversight and feedback in an automated system. That’s the lens of this show: AI is powerful, but humans aren’t leaving the loop. Not yet. Maybe not ever.
This isn’t another “AI is going to change everything” podcast. It’s for builders, operators, and the AI-curious who are tired of breathless hype, doomerism, and surface-level news recaps with no original thought.
We run through the week's AI headlines and make the call: is this actual signal worth paying attention to, or just noise clogging the timeline?
A real use case or product idea lands on the table. We debate whether it's worth building now or if the tech isn't there yet.
Take a complex AI concept and explain it the way you'd actually explain it to a non-technical stakeholder. No jargon allowed.
One tool, library, or workflow change we actually adopted this week. No sponsorship energy. Just what's in the trenches.
AI Engineer & Entrepreneur
AI Engineer and entrepreneur. He lives in the intersection of engineering and businesses.
Serial Builder & Relentless Executor
Serial Builder and relentless executor. He comes from the lens of what works and what doesn't.
Six weeks ago Anthropic said a model was too dangerous to ship. This week they shipped Opus 4.8, called it near-Mythos, and said Mythos-class models reach every customer in the coming weeks. Was it ever that dangerous? We make the call.
My First Million Ep 822
Avoca's $125M raise
Circle Agent Stack
Oscar“Too dangerous to ship" was never a safety call. It was a 90-day enterprise head start.”
Matt“Devin at $26B is the top, not the floor. An agent lab with no distribution is the WeWork of 2026.”
Cursor just shipped a coding model that matches Claude Opus 4.7 at one tenth the price, built on an open Chinese base model. The same week, Anthropic is closing a $30B round at a $900B valuation. If frontier coding got commoditized in seven days, what is anyone paying premium for?
Welcome to Human In the Loop, a weekly podcast where two builders cut through the AI hype cycle. No breathless hype. No doomerism. No surface-level recaps. Honest, opinionated conversations from people actually building with AI.
a real replacement for `/compact`
Oscar“Cursor Composer 2.5 just proved the open base model thesis. Coding-as-a-service is about to fall off a cliff in price.”
Matt“Karpathy joining Anthropic is worth more than the $900B valuation as a signal. Talent is the only moat the market still underprices.”
Three months ago on Episode 1, we asked if there was a real business in selling AI to small businesses. This week, Anthropic shipped it themselves. So we just watched the founder playbook get eaten by a frontier lab in 90 days. If you were six weeks into building that company, what do you do Monday?
15 agentic workflows, QuickBooks + HubSpot + Microsoft 365 connectors, 10-city US tour.
276B MoE, 0.4s full-duplex response, Mira Murati throws shade at every other lab's voice stack.
$150M ARR, 40% of the Fortune 50 paying for customer agents.
Driven by national-security fears around Anthropic's Mythos model.
On the same morning it posts record revenue — the first big “AI did it” layoff that isn't a cover for bad numbers.
The word every vendor abuses — and how to tell the real ones from the chatbots in costume.
What “AI plugged into your tools” actually requires.
What to ask when a vendor pitches a voice agent.
Oscar“Anthropic just turned every AI consultant into a reseller. By Q3, the model providers own the workflow layer for every regulated and semi-regulated vertical.”
Matt“Every vendor calling their thing an ‘AI agent’ in 2026 is going to look like every vendor that called their thing ‘cloud-native’ in 2015. By Q4 the term means nothing.”
On May 12, 2026, Jackson Oaks — founder of Recursion AI and the self-hosted AI platform Courier — joins the show. Jackson has been running open-source models in production for SMBs since early 2025, back when most of the industry still called local inference a hobbyist toy. Today his company runs production workloads on Apple Mac hardware, processes 600 to 800 thousand API calls a month per machine, and is profitable doing it.
His thesis: eighty percent of businesses have eighty percent of use cases that don't need Opus or GPT-5.5. They need a smaller open-source model, good systems, and predictable pricing. Frontier intelligence, or boring infrastructure? Per-token billing, or a flat rate on hardware you already own?
That's the cold open. Every fifth episode of Human In The Loop is a guest deep-dive — no Signal or Noise, no rotating segment, one topic, one expert. Oscar, Matt, and Jackson spend 58 minutes on what most AI bills are actually paying for, and close with three hot takes you won't hear anywhere else.
Where local models win, where frontier models still matter, and how to tell which category your use case is in.
Time bought back, margin protected on AI products, conversion lift on AI features — and which one is nearly impossible to measure honestly.
Why M-series is the most underrated AI hardware story of the decade. 1/10th the cost of NVIDIA, 30 to 40x more power efficient. Apple has been positioning for this since the M1 dropped — the same week ChatGPT did.
600 to 800,000 API calls a month on a single Mac Studio. Flat-rate cloud pricing starting at $100/mo for 45 to 100K calls. The math on why predictable beats per-token for SMBs.
A Fortune client paid Deloitte $400,000 for what turned out to be a GPT wrapper with an unoptimized RAG database. MIT says 95% of business AI pilots can't measure ROI. We have theories.
The infinite hallucination loop that ate 10,000 requests in a week. Building hallucination detection from scratch. The fine-tuned 14B model that outperformed GPT-4o on a real production task because the data was good and the task was narrow.
Idempotency in non-deterministic systems. Observability. Redundancy. Why your AI feature needs the manual OCR backup you were about to delete.
Why the next wave of AI businesses isn't “AI for everything” — it's $200/mo agents for pressure washers, plumbers, landscapers, attorneys, accountants. Specialize down, charge real money, capture real value.
Matt“One of Anthropic or OpenAI buys the other — or merges with a foreign lab — inside three years. Or open-source overtakes both and they shrink to a fraction of their current valuations. Their burn rate is not sustainable.”
Oscar“Every home will eventually have a Mac Mini running a better Alexa, powered by open-source models — not closed-source ones. That future is closer than people think.”
Jackson“Better systems and structure with smaller open-source models beat throwing frontier models at unstructured problems. People are compensating for a lack of system with a bigger model. We're doing the opposite — we're building better systems so we can use smaller models.”
On April 24, 2026, an AI coding agent hit a credential mismatch in a staging environment. Nine seconds later, the entire production database of a company called PocketOS was gone. Backups too. The agent confessed: “I violated every principle I was given.” The model was Claude Opus 4.6.
Five days later, on April 29, Bloomberg and CNBC reported Anthropic was weighing offers at a $900 billion valuation. Roughly $50 billion in new capital. A round that would put the lab behind Claude above OpenAI as the most valuable AI company in the world. Two stories. Same week. Same lab. We call every one.
That's the cold open. From there, Oscar and Matt spend 46 minutes doing what this show does: filter the week's AI noise, debate three real business ideas, and close with two hot takes you won't hear anywhere else.
$50B raise on the table. Run-rate revenue at $30B. The Mythos withholding story we called in Episode 1 was the brand. The Google $40B in Episode 3 was the funding story. This is the receipt. Treat your model spend like an interest rate, not a software line item.
Nine seconds. Backups gone. The agent went looking for an API token, found one in an unrelated file, and used it. The token was scoped for any operation, including destructive ones. Three holes in the swiss cheese. The agent walked through all of them.
Beijing killed Meta's $2B Singapore-routed AI deal on April 27. Meta acquired humanoid-robotics startup Assured Robot Intelligence on May 1. The thesis didn't change. The substrate did. Robotics is the next frontier-model fight.
Agents can now create accounts, register domains, start paid subscriptions, and deploy apps with no human in the loop. Default spend cap is $100 per provider per month. The PocketOS story is the demand signal for spend caps and audit logs.
The Hangzhou Intermediate People's Court upheld a ruling that Zhou, a QA supervisor verifying LLM outputs, couldn't be fired or pushed to a 40% pay cut just because AI took over his work. First major court ruling anywhere putting limits on AI-driven layoffs.
Per Gustaf Alströmer's RFS. Don't sell SaaS to insurance brokers, accountants, or compliance teams. Become the broker. File the taxes. Run the audit. Charge services prices for AI-margin work. The wedge is bigger than the entire SaaS market. Pushback: you stop being software and start being ops, with E&O liability and license requirements baked in.
Per Tom Blomfield's RFS. The blocker to AI automation isn't the models anymore. It's domain knowledge scattered across heads, email, Slack, tickets, and databases. Build the layer that pulls fragmented company knowledge, keeps it current, and turns it into an executable skills file for agents. Pushback: this is wikis 5.0, and Microsoft and Notion eat the category as a feature in 18 months.
Per Tyler Bosmeny's RFS. $500K interceptors don't work against $500 drones. Build the Cloudflare-shaped layer for swarm defense: distributed sensors, software-first interceptors, autonomy-stack attacks. The thesis is real. The dual-use moral question is not optional.
Oscar“Anthropic at nine hundred billion dollars is the moment the labs stopped being labs. They're sovereign wealth funds with a research division attached. The Mythos withholding story we called in Episode 1 was the brand. The fundraise is the receipt. Price your model spend like an interest rate, not a software line item.”
Matt“Every AI agent in production is one bad scope away from being the PocketOS story. The fix isn't better models. It's permissions, audit logs, and a human approval gate on every destructive operation. If your agent can drop a database, your agent will drop a database. The question isn't if. The question is on what week.”
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