Dasith Wijesiriwardena

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Dasith Wijesiriwardena

Dasith Wijesiriwardena

@dasiths

Developer, blogger, tech speaker with unhealthy focus on distributed systems, overly keen problem solver and improving cricketer. Snr Engineer @Microsoft.

Melbourne, Australia Tham gia Nisan 2009
580 Đang theo dõi328 Người theo dõi
Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
Just launched PromptyDumpty - a universal package manager for AI agent artifacts! 📦 Install & share prompts across #coding #agents 🔄 One package format, works everywhere 🎯 Auto-detects your #AI agent 🧹 Clean install/uninstall tracking Learn more 👉 dumpty.dev
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Philipp Schmid
Philipp Schmid@_philschmid·
The hottest discussion in AI is about "context engineering". But what is it? Do we need it? Context engineering isn't about crafting better prompts. It's building dynamic systems that provides the right information at the right time. Think of an AI assistant asked to schedule a meeting. → Poor Context: It only sees the request. The result is a robotic, unhelpful reply. → Rich Context: It sees the request PLUS your calendar, past emails, and available tools (like send_invite). The result is a "magical" assistant that proactively solves the problem. The future of AI agents isn't about perfect prompts. It's about perfect context.
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vas
vas@vasuman·
I promise you you’re vibe coding wrong as someone who has built multiple production-ready applications, with thousands of users, from just Cursor with minimum intervention. But first here's you (probably): You open Cursor. Type “build me X.” It spirals. Nothing works. You start over. That’s not development. That’s chaos. I have an incredibly simple system that works every single time:
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
I've been doing some vibe coding experiments recently and came up with this pattern I call "breadcrumbs" that's giving me consistent results. The Breadcrumb Protocol is designed to help you vibe code by creating a shared scratchpad. youtu.be/etYG-6-9Mlk
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
#dapr-agents let developers design, test, and deploy agents that integrate seamlessly as collaborative services in larger systems, without reinventing microservices. I've done some experiments here. github.com/dasiths/llm-pl…
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
I'm really excited for the idea behind Anthropic's Model Context Protocol (#MCP) but have some reservations about the execution. There are some limitations that make it a non starter for enterprise right now. One of those is Authn/Authz. github.com/modelcontextpr…
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
@nickchapsas I wanted to reach out regarding the practice of running migration as part of your app init which is considered a bad practice (concurrency, elevated permissions). A caveat in the video description would help teams. See #issuecomment-328154355" target="_blank" rel="nofollow noopener">github.com/dotnet/efcore/…
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
My team recently concluded a project that used #promptflow. There were some learning around optimizing for throughput and latency. We developed an awesome little throughput testing kit for pf-serve and contributed it to the Promptflow OSS repo. github.com/microsoft/prom…
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
@davidfowl Haven't done this for .NET 8 but would keyed services help with this scenario where you need a tenant aware IOptionsMonitorCache for example? as shown here #61730788" target="_blank" rel="nofollow noopener">stackoverflow.com/questions/4959…
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David Fowler
David Fowler@davidfowl·
Is anyone using keyed services for multi tenancy in .NET 8 applications?
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Dasith Wijesiriwardena đã retweet
Yann LeCun
Yann LeCun@ylecun·
As long as AI systems are trained to reproduce human-generated data (e.g. text) and have no search/planning/reasoning capability, performance will saturate below or around human level. Furthermore, the amount of trials needed to reach that level will be far larger than the amount of trials needed to train humans. LLMs are trained with 200,000 years worth of reading material and are still pretty dumb. Their usefulness resides in their vast accumulated knowledge and language fluency. But they are still pretty dumb.
Pedro Domingos@pmddomingos

Interesting how in all these domains AI is asymptoting at roughly human performance - where's the AI zooming past us to superintelligence that Kurzweil etc. predicted/feared?

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Erik Meijer
Erik Meijer@headinthebox·
Legit question. What is the value of frameworks like LangChain, Autogen, crewAI, ... that basically build the same abstractions on top of a programming language that the underlying programming language already supports. For example chaining is sequential composition, agents in multi-agents frameworks are just objects (or if you want to be fancy actors) and interaction patterns are just control flow. What's wrong with just writing code. Since these frameworks are so popular, there must be some deep attraction or advantage to using them. Maybe if you would actually design a completely new language that supports these notions, that might be something. But even then I seriously doubt that the switching costs are worth it. What am I missing?
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
@reubenbond @headinthebox (cont) with strong opinions and build features like serving (http server) on top. They are great for building POC like things but don't offer the engineers enough control to leverage mature patterns or eject from the pigeonholed architecture enforced by the LLM agent frameworks.
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Dasith Wijesiriwardena
Dasith Wijesiriwardena@dasiths·
@reubenbond @headinthebox Having worked with "big" customer recently, most teams that develop LLM solutions aren't cross functional. Most orgs still deal with DS folks who do most of their work on Jupyter notebooks. Frameworks like PromptFlow try to solve this by giving large building blocks (cont...)
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