3 AImigo
A weekly podcast about how engineers and companies work with AI.
About the podcast
We discuss how to measure AI’s impact on software development, rethink hiring, and decide what to delegate to agents. Once a month, we cover the latest AI news and what it changes for engineering teams.
Hosts
All episodes
Infrastructure for Agent Development
Alexander Polomodov, Evgeny Sergeev and Aleksey Litvinov discuss development infrastructure as the number of agents grows.
October 2026 AI Digest: Anthropic IPO, New Models and Agent Security
Alexander Polomodov, Evgeny Sergeev, and Aleksey Litvinov discuss October's AI news: faster vulnerability discovery, the economics of AI labs, and new models.
The AI-Native State: What It Is and Where the Boundary Lies
Can the AI-native company model transfer to government? Evgeny Sergeev, Aleksey Litvinov, and Alexander Polomodov discuss agency goals, the citizen journey, and the difference between employee assistance and autonomous execution of rules.
Agents with Payment Authority: Would We Trust AI with Our Money?
How can we delegate an entire purchase to an agent? The co-hosts begin with family groceries, Vinted searches, and unnecessary extension leads in an order. Discovery, selection, negotiation, order approval, and payment require different permissions; a budget cannot replace knowledge of personal preferences.
What Can We Trust an AI Agent With? Boundaries of Autonomy
What does it mean to delegate a task, a role, or an end-to-end outcome to an agent? The co-hosts examine autonomy through content releases at Flo Health, a game migration between platforms, and the creation of podcast covers.
AI-Native: What Does It Mean for a Company?
What distinguishes an AI-native company from a team where everyone uses AI? The co-hosts compare three perspectives: agents working across employees, a path from intent to outcome with fewer manual handoffs, and redesigning the overall system in which people and agents work together.
September 2026 AI Digest: Cheaper Generation, Costlier Verification
The September digest moves the conversation from the models themselves to the systems around them: OpenAI sells the Codex harness as the Agents API, providers push cloud agents and new plans, and agents gain traces, policies, and outcome metrics like production services.
How to Keep Up with AI Changes Without Draining Your Energy
Models, agents, and research arrive faster than anyone can evaluate them. Chasing every update takes time away from practice and independent thought.
A Junior Without Easy Tasks. How Do You Enter Tech in the AI Era?
Building a product is easier, but landing a first engineering job is harder: AI takes over the small tasks that once trained new engineers.
AI Hires AI. How Do We Redesign Tech Interviews?
AI now participates on both sides of hiring, so banning a tool cannot restore the old signal: résumés and familiar online stages increasingly fail to predict performance in the role.
August 2026 AI Digest: Cheaper AI, Harder Adoption
Six connected stories from August reveal the same shift: access to models is getting cheaper while building a working AI system is getting harder.
AI Writes More Code. Why Doesn't Delivery Speed Up?
AI can make an individual engineer write code much faster, yet a higher volume of changes does not by itself shorten end-to-end delivery of value to users.
Where AI Stands in Software Development
The first 3 AImigo conversation compares three practical lenses: AI4SDLC, AI-Assisted Engineering adoption, and management of a large engineering organisation.