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Agents & Crumbles

Where agentic engineering meets real-world strategy.

A podcast for founders, CTOs, and engineering leaders navigating the agentic AI era. Each episode unpacks a real challenge in AI strategy, agentic engineering, or the shifting landscape of software development. Solo episodes deliver deep technical insight. Guest conversations bring operator-level experience from people building and shipping AI-native products.

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Agents & Crumbles

with Krishna Halaharvi

About the Host

Hosted by Krishna Halaharvi, an AI-First Fractional CTO with 13+ years building engineering teams at enterprise scale. Krishna brings an opinionated, practitioner-first perspective grounded in real experience scaling AI systems, establishing governance frameworks, and leading engineering organizations through the shift to AI-native development.

Technically credible but accessible
Opinionated with evidence
Practitioner-first

What We Cover

Every episode maps to one of four content pillars that connect directly to the challenges engineering leaders face today.

Agentic Engineering

Agent design patterns, tool-use, planning, memory, multi-agent orchestration, and building reliable agent pipelines for production.

AI Strategy & Enablement

AI readiness assessment, adoption metrics, build vs. buy decisions, governance frameworks, and ROI models for AI investments.

The Shift in Software Engineering

AI-augmented development, team structures for AI-native orgs, the evolving CTO role, and platform engineering in the age of agents.

Fractional CTO Playbook

What a fractional CTO actually does in week 1, building governance from scratch, pricing, positioning, and real engagement stories.

Episode Format

Two distinct formats, each serving a different purpose. Every episode features “The Crumble” — what old assumption is breaking apart because of this topic.

Solo Episodes

15-25 minutes

Deep dives into frameworks, original thinking, and unfiltered takes on industry shifts. This is where signature concepts like the AI Readiness Matrix get introduced and real architectural decisions get broken down.

Guest Episodes

30-45 minutes

Conversations with AI/ML engineering leaders, startup founders, developer tool builders, and enterprise AI leaders. Operator-level stories from people building and shipping AI-native products.

First Episodes

The first three episodes are designed to establish the show premise, demonstrate deep technical credibility, and give listeners immediate value.

1

Why Every CTO Needs an Agentic Strategy

18-22 min
Agentic Engineering + AI Strategy

A Series B startup built a demo agent in a hackathon, got their board excited, and then spent 6 months unable to get it to production. What went wrong? They had a technology project without an agentic strategy.

What agentic engineering actually means in 2026
The three layers every agentic strategy needs: infrastructure, orchestration, and governance
Why most companies fail at the transition from demo to production
The AI Readiness Matrix framework
2

Vector Databases Are Not Your Strategy

18-22 min
Agentic Engineering

Every pitch deck in 2026 mentions vector databases. But companies spend months optimizing their embedding strategy when their real problem is that their data is garbage.

The vector database landscape: what has changed and what consolidation tells us
When you actually need a dedicated vector DB vs. when pgvector is enough
The retrieval pipeline matters more than the database
Cost modeling: what vendors tell you vs. your actual bill at scale
3

AI Adoption Metrics That Actually Matter

20-25 min
AI Strategy & Enablement

A CEO asked me last month, "How do I know if our AI investments are working?" Their team had shipped 4 AI features and had no idea if any of them were actually moving the needle.

Why vanity metrics fail: "we shipped 4 AI features" tells you nothing
Three tiers of AI adoption metrics: adoption, effectiveness, and business impact
How to build an AI metrics dashboard with specific KPIs
The AI-First Maturity Model (AFMM) framework

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