Show Notes
Pushing through the AI flood in coding doesn’t have to be chaotic. In this video, the focus is on sticking to primitives, building robust workflows, and using AI to augment, not replace, your engineering judgment.
Core mindset: primitives, patterns, and guardrails
- The safest path forward is choosing tools that won’t get obsolete overnight and pairing them with stable workflows.
- Don’t offload everything to AI. Offload workflows, not decisions. Build objective, deterministic parts and leave higher-level goals to AI-assisted planning.
- Design for modularity: think in Lego blocks and feature flags so users can unlock capabilities over time without a full front-end rewrite.
Generative UI, diffusion, and practical implications
- Diffusion and advanced models push toward a future where UI components, data streams, and workflows can be streamed in or composed on demand.
- A practical pattern: a tool call + validation (e.g., TypeScript + Zod) + LLM to decide what to do. The demo concept (streaming UI components) is compelling, but you still need deterministic parts for reliability.
- For SaaS products, imagine feature flags that expose additional capabilities behind the scenes. The front-end can surface these once the API support and testing exist, improving retention and user customization.
Concrete tooling signals to act on now
- VS Code is accelerating with instruction files and native instruction handling, plus improved agent mode.
- Use an instructions directory in your Git repo to define context-specific rules and prompts.
- Leverage profiles to keep stacks (linting, extensions, layout) tuned for each task (e.g., Python, frontend).
- Explore agent mode for automated flows, test integration, and running change logs automatically.
- A simple, practical approach to context and prompts is becoming more viable with native support for instructions and curated prompts.
- A note on momentum: wide adoption of these patterns will require guard rails and careful testing—don’t chase every new model; integrate what genuinely adds reliability.
Notable builds and ideas worth watching
- Generative UI demos (e.g., streaming components for tasks) hint at how interfaces could adapt as you define goals and actions.
- The idea of “Lego API blocks” where a SaaS provider exposes built-in features and lets users enable additional capabilities via UI-driven configuration.
- A more mature ecosystem could include automated, in-app roundups and digest channels to keep communities and teams aligned with AI progress.
Ecosystem tools and community automation
- Discord automations are a focus: building digest bots to summarize daily/weekly AI news and updates so members don’t miss critical shifts.
- A practical example: a news roundup bot (the “news bird”) that curates trusted sources and answers questions about AI trends on demand.
- Lightweight, maintainable workflows in your community can scale better than posting every day—use automation to surface what matters.
Open source strategy and collaboration
- Open-source templates are on the agenda (e.g., project skeletons for multi-agent setups, content automation pipelines, and a prompt library).
- Projects mentioned as inspiration:
- MAP: a B2C multi-agent platform
- echko: B2B content automation
- Prompt library: a growing collection of prompts with automated checks
- The plan includes contributor-friendly structures: issue templates, project templates, single sign-on with Discord, and a shared organization for collaboration.
- The goal is to surface real collaboration: watchers and tooling that invite others to contribute, review, and extend.
Rebranding and audience shift
- Considering a rename to reduce confusion around terms like “vibe” and to attract:
- engineers and engineer-adjacent professionals who want to leverage AI effectively
- business owners who are committed to investing time to gain AI-driven value
- The content strategy will emphasize learnings from applying tools, not just day-to-day news.
Actionable takeaways
- Focus on durable primitives:
- Build with stable APIs and guardrails; avoid over-reliance on any single AI capability.
- Use feature flags to unlock capabilities progressively.
- Adopt practical workflows now:
- Start using VS Code instruction files and the agent-mode workflow to streamline your prompts and actions.
- Create a small set of reusable prompts and validations (e.g., Zod schemas) to reduce nondeterminism.
- Improve your community experience with automation:
- Implement a digest/news bot to surface the most impactful updates for your team or community.
- Explore open-source collaboration:
- Set up project templates and issue templates to invite contributions.
- Prepare a clear path for non-contributors to engage, while enabling members to contribute code and content.
Links
- Wappalyzer (tool to analyze a website's tech stack)
- VS Code (instruction files and agent-mode enhancements)