TLDRocket
Sign in

Agent Infrastructure

209 summarised stories about Agent Infrastructure, each linking back to the original source. Browse all topics →

+ Follow this topic

Wednesday, 1 July 2026

Autoresearch: The feedback loop behind self-improving agents

Latent Space 3 months ago 48 ● 2 sources

Introspection, a startup founded by former xAI employees, is building infrastructure for "autoresearch" systems where agents maintain and improve themselves through feedback loops rather than requiring constant human intervention. The company proposes three patterns: treating the feedback loop itself as the product, using "agent recipes" to capture how systems evolve over time, and optimizing for systems that become both better and cheaper as they operate. Companies deploying these self-improving agents will need to establish reliable feedback signals, control costs, and gradually shift human involvement from direct decisions to providing training data and oversight.

How we really build production-grade AI agents: beyond models, toward data and API quality

Postman Blog 3 months ago 25

Teams building AI agents typically fail in production because they over-index on model intelligence while neglecting data quality, API reliability, and execution governance. Agent performance in production depends primarily on three coupled systems—data quality, API quality, and execution quality—rather than model capability alone, with most failures stemming from interface issues rather than reasoning failures. Success requires treating agents as distributed systems embedded in execution workflows with full observability and governance, rather than conversational interfaces relying on strong models compensating for weak tools and incomplete data.

The daily briefing

Every AI story that matters, in your inbox by 8am.

TLDRocket reads all relevant sources, removes duplicate coverage, and summarises the day in two minutes. Follow companies and topics for alerts, or get the briefing in Slack. Free, no spam, unsubscribe anytime.