About this channel
Building with AI is the organising theme of DeepLearningAI. Courses, instructional videos and material from developer events cover coding agents, data engineering and assistants that can remember…
Building with AI is the organising theme of DeepLearningAI. Courses, instructional videos and material from developer events cover coding agents, data engineering and assistants that can remember information or learn from experience. The channel addresses the choices involved in making an AI application work: where a model runs, how a task is specified and how the developer keeps control of the process. Local AI sits alongside more demanding uses of frontier models, giving the subject both a device-level and a broader development perspective.
A full course on specification-driven development examines a workflow in which explicit requirements guide coding agents. An episode about assistants with on-device memory takes the discussion towards systems that retain context close to the user. Material on image and video generation extends agent development into creative applications. These are concrete building problems, with the emphasis on how components and workflows fit together rather than simply announcing another model.
The selection also includes examples from the developer community. A voice AI project in which an agent calls a developer before deleting records illustrates the role of human intervention in an automated workflow. Event coverage and shorter introductions sit beside longer teaching formats, allowing viewers to encounter a concept before committing to a course. Developers and technically curious learners can use the channel to choose a subject to practise, while people already experimenting with coding agents can explore more deliberate ways to specify, supervise and extend their systems.
Latest episode
Full Course: Spec-Driven Development with Coding Agents
Vibe coding is fast, but it often produces code that doesn't match what you asked for. Spec-driven development is the disciplined alternative: write a clear markdown spec defining what to build, and…
Vibe coding is fast, but it often produces code that doesn't match what you asked for. Spec-driven development is the disciplined alternative: write a clear markdown spec defining what to build, and let your coding agent implement it.
Earn your certificate here: https://bit.ly/4hmJc2K
You'll learn to:
- Write a project constitution defining mission, tech stack, and roadmap
- Plan, implement, and validate features using a spec as the agent's guide
- Introduce SDD to a legacy codebase
- Package your workflow into an agent skill that's portable across agents and IDEs
Spec-Driven Development with Coding Agents is built in partnership with JetBrains and taught by Paul Everitt, Developer Advocate at JetBrains.
Recommended: basic familiarity with a programming language and experience with LLM-based coding tools.
YouTube Shorts
uploads
More episodes from this channel
Build Your Own App In Just 30 Minutes! Full Course with Andrew Ng
2.6.2026
Earn your certificate here: https://bit.ly/4ejb47H If you’ve never written code before, this course is for you. In less than 30 minutes, you’ll learn to describe an idea in words and let AI transform it...
AI Dev 26 x SF | Ara Khan: Evals Are Broken Use Them Anyway
22.5.2026
This talk by Cline's Ara Khan explains why they went from "evals are useless" to using them as a core part of my agent improvement loop. I share practical heuristics for interpreting, running, and...
AI Dev 26 x SF | Andi Partovi: Why Every Agent Needs a Simulation Sandbox
22.5.2026
AI agents fail in unpredictable ways that traditional testing can't catch — hallucinations, wrong tool calls, policy violations, and more. Teams only discover these failures after users hit them in production. A simulation sandbox...
AI Dev 26 x SF | João Moura: Building Recurring, Governed, and Embedded Enterprise Workflows
22.5.2026
Modern enterprises don't struggle to experiment with AI — they struggle to operationalize it reliably. In this talk, CrewAI's CEO outlines how leading organizations are moving beyond one-off automations to build recurring, governed, and...
AI Dev 26 x SF | Luke Kim: The Agent Data Stack—Why Every AI Agent Needs Its Own Data Stack
22.5.2026
From centralized to distributed: In the old world, organizations relied on one centralized data and AI platform. In the new world of AI agents, every agent needs its own sandboxed, secure, and modern data...
AI Dev 26 x SF | Manos Koukoumidis & Stefan Webb: VibeML: Build your AI model in hours, not months
22.5.2026
The next major shift in enterprise AI is underway; enterprises are moving from generic AI they rent to specialized AI they own. The benefits are clear: higher quality, dramatically lower costs, full control, and...
AI Dev 26 x SF | Daniel Beutel: Flower SuperGrid Agents
22.5.2026
At AI Dev 26 x San Francisco, Flower Lab's Daniel Beutel talked about Flower SuperGrid, the industry standard for Federated AI. With SuperGrid Agents, you can now build and run context-rich agents that learn...
AI Dev 26 x SF | Or Dagan: Optimizing Accuracy, Cost, and Latency in Real-World Agents
22.5.2026
Most agentic systems rely on hardcoded heuristics to navigate execution decisions (e.g. which models, tools, and test-time compute scaling approaches to use) leading to efficiency leakage across cost, latency and accuracy. AI21 Maestro optimizes...
AI Dev 26 x SF | Andrew Filev: Multi Model Pipelines—How to Get Better AI Results for Less
22.5.2026
In this talk by Zencoder's Andrew Filev, attendees learned how decomposing tasks into pipelines and dynamically routing them across models improves quality, reduces cost, and makes AI systems more reliable.
AI Dev 26 x SF | Diamond Bishop: The Next 100 Agents. Building the Agent Native Office
22.5.2026
Building your first agent is exciting. Building a platform that can evolve into an office where dozens of teams can safely deploy their own agents is a different beast entirely. In this talk, Diamond...
AI Dev 26 x SF | Paul Everitt: The Shift to Agentic Engineering
22.5.2026
More code, fewer staff — the industry is on a bender. But what about quality? At AI Dev 26 x San Francisco, Paul Everitt from JetBrains discussed the rise of agentic engineering and how...
AI Dev 26 x SF | Andrew K. Davies: Deterministic Memory: How to Build an AI That Cannot Lie
22.5.2026
What if your AI's memory was mathematically verifiable? What if every retrieval was provenance-backed, every result bit-exact and cryptographically reproducible? OnMemory.ai introduces deterministic semantic memory built on E8 lattice quantization, replacing probabilistic vector search...
AI Dev 26 x SF | Thierry Damiba: Edge to Cloud Video Anomaly Detection
22.5.2026
This talk by Qdrant's Thierry Damiba shows how to build a real-time video anomaly detection system that works in open-world settings, where the most important events are often the ones you did not explicitly...
AI Dev 26 x SF | Brandon Waselnuk: Building the Context Engine AI Agents Need
22.5.2026
Every AI coding tool can generate code. Very few can generate the right code for your organization, because they're missing context. They don't know why your team chose Redis over DynamoDB, what the team...
AI Dev 26 x SF | Jerry Liu: My Agent Can't Read a PDF?
22.5.2026
The future of automating knowledge work depends on AI agents that can reliably read and understand documents — but today's agents struggle with complex layouts, tables, and visual elements. This talk by LlamaIndex' Jerry...
AI Dev 26 x SF | Ashwyn Sharma: Every App Needs a Voice UI. Here's How to Build It
21.5.2026
Voice AI today is mostly customer service bots. That's about to change — and AI devs will build what comes next. This talk by Vocal Bridge's Ashwyn Sharma introduces Voice UI as an emerging...
AI Dev 26 x SF | Atai Barkai: Fullstack Agents & Generative UI with AG UI
21.5.2026
All UI will be AI. In this talk, Atai Barkai from CopilotKit explored the emerging space of Generative UI, and went over the practical building blocks emerging in the space.
AI Dev 26 x SF | Idan Raman: The Identity Crisis of Browser Agents
21.5.2026
As computer-use models become smarter, the bottleneck for their adoption is becoming clear: 20 years of web identity tech must be securely adapted for AI agents. In this talk, Idan Raman from Anchor Browser...
AI Dev 26 x SF | Tom Howlett: Can LLMs Generate Enterprise Quality Code?
21.5.2026
We all know how fast it is to create an app with modern AI agents but how do we ensure the code is reliable, maintainable and secure enough to be used by enterprises? In...
AI Dev 26 x SF | Erik Thorelli: Deploying AI Code Review at Scale
21.5.2026
AI coding tools have dramatically increased developer velocity, but they haven't eliminated the need for code review. In fact, they've made it more critical than ever. In this session, Erik Thorelli, Developer Experience Lead...
Innohub TV
Watch this content also on Innohub TV
We picked clips from Innohub TV that continue the same topic.
