Talk topics

Three talks, each with a different mission profile.

The topics are arranged like launch paths so conference organizers can immediately see which audience each one serves.

TALK-01

Production AI Is Nothing Like Demo AI

AI agent conferences, engineering leadership summits, startup operator events

A field guide for agent reliability, observability, escalation, and executive trust.

TALK-02

The New Staff Engineer: Architect, Evaluator, Operator

Labs, engineering orgs, universities, founder communities

How senior technologists create leverage when AI writes more of the code.

TALK-03

From India Founder to Apple Staff Engineer

Universities, developer communities, early-career technologists

A practical reinvention story for young technologists building ambitious careers.

Agent conferences
Engineering leadership
AI startup summits
Universities
Developer communities

Why Invite Rahat

The strongest talks combine AI systems depth, executive relevance, and a human story that makes ambition feel reachable.

SIG-01

Conference organizers

Clear abstracts

Talks are framed as practical operating systems for agent reliability and senior technical judgment.

SIG-02

AI startups

Executive relevance

The material connects technical depth to trust, cost, product risk, and enterprise adoption.

SIG-03

Labs and teams

Systems credibility

The perspective spans agent traces, evals, guardrails, memory, and human escalation.

SIG-04

Students

Human inspiration

The career story becomes a useful path, not just a motivational anecdote.

Speaker Bio and Promise

Short and long bio variants can be copied into conference CFPs and event pages.

Short bio

Rahat Khanna is a Staff Software Engineer focused on AI agent infrastructure, evaluation, observability, and enterprise-ready autonomy. His work bridges Apple-scale platform engineering, founder experience, and a long-term thesis across agents, humanoids, and space.

Audience promise

Audiences leave with practical patterns for moving from impressive AI demos to reliable systems: traces, evals, guardrails, supervision, cost visibility, and leadership judgment.

TAKEAWAY-01

A clearer mental model for production agents

Why the shift from demo AI to deployed autonomy depends on observability, evaluation, guardrails, and escalation.

TAKEAWAY-02

Practical language for executive decisions

How leaders can discuss agent quality, cost, risk, and adoption without getting lost in hype or implementation detail.

TAKEAWAY-03

A human story of technical reinvention

How founder roots, Apple-scale systems, and the AI shift can inspire builders to take larger swings.

Speaker Kit Copy

Public-safe bio variants for event pages, CFP submissions, podcast intros, and university programs.

Short bio

Rahat Khanna is a Staff Software Engineer focused on AI agent infrastructure, evaluation, observability, and enterprise-ready autonomy. His work spans founder/CTO execution, Flipkart-scale commerce systems, Apple-scale web platforms, and production AI reliability patterns. He speaks about moving from demo AI to trustworthy autonomous systems.

Medium bio

Rahat Khanna is a Staff Software Engineer focused on making AI agents reliable, observable, and enterprise-ready. His career spans founder and CTO work, fintech infrastructure, enterprise transformation, Flipkart-scale commerce systems, and Apple-scale web platforms across ads and media products. His current thesis is that production AI needs a reliability stack: traces, evals, guardrails, supervision, cost visibility, and human escalation. Rahat speaks to builders, executives, and students about the shift from impressive AI demos to inspectable autonomous systems, and about how young technologists can build durable careers in the AI era.

Extended bio

Rahat Khanna is a Staff Software Engineer focused on AI agent infrastructure, evaluation, observability, guardrails, and enterprise-ready autonomy. His career began as a founder and CTO, building hundreds of websites and enterprise applications and helping architect fintech infrastructure that handled large-scale transaction volume. He later worked across enterprise transformation, Flipkart-scale commerce systems, and Apple-scale web platforms for ads and media products. Rahat's current work and public thesis center on the reliability layer for autonomous systems: traces, evals, memory, tool policy, supervision, cost and latency visibility, and human escalation. He is interested in the intersection of AI agents, humanoids, space, and human potential because each domain raises the same question: how do we trust autonomous systems when the stakes keep increasing? His talks connect technical depth, executive judgment, and an honest career story for ambitious young technologists.

Talk Abstracts

Each abstract is framed for organizers who need a clear title, audience fit, and practical audience takeaways.

TALK ABSTRACT 01

Production AI Is Nothing Like Demo AI

AI agent conferences, applied AI summits, engineering leadership teams

A practical talk on the gap between impressive agent demos and production-grade autonomy. The core argument: agents become useful only when their behavior is observable, evaluable, governed, and easy to escalate to humans.

Trace-first operationsEvaluation as risk languageHuman escalation as product surface
TALK ABSTRACT 02

The New Staff Engineer: Architect, Evaluator, Operator

AI labs, engineering organizations, universities, founder communities

A leadership talk on how senior engineers create leverage when AI writes more code. The role shifts from only building features to designing systems of judgment: harnesses, evals, policies, workflows, and feedback loops.

Leverage through system designEvaluation-first leadershipMentorship during the AI shift
TALK ABSTRACT 03

From India Founder to Apple Staff Engineer

Universities, developer communities, early-career technologists

A human and technical story about reinvention: founder roots, high-scale systems, Apple-scale platform work, and the current AI infrastructure chapter. The talk is designed to make ambitious technical growth feel reachable and practical.

Career reinvention patternsFounder-to-platform lessonsBuilding confidence through real systems

BOOKING PATH / DIRECT SIGNAL

Invite Rahat to speak.

Best fit: AI agent infrastructure, developer tools, engineering leadership, startup AI strategy, and student inspiration events.

Include audience, event date, format, and the strongest talk fit.
Send invitation