Alex LongDistance

🚀 Building the next big thing, one code at a time. 🐶

[Aiswarya Venkitesh @AiswaryaVenkit1]

🚀 Microsoft is evolving… and it’s bigger than you think

We’re moving from AI Assistants → Autonomous Work Agents
And this shift is changing how work actually gets done.

💡 What’s new with Microsoft Copilot?

🔹 Works across Word, Excel, PowerPoint seamlessly
🔹 Automates repetitive tasks (finally!)
🔹 Executes multi-step workflows end-to-end
🔹 Provides advanced reasoning for complex problems
🔹 Remembers preferences for personalized responses

📊 But it doesn’t stop there…

✔️ Cross-app automation (Word + Excel + Teams)
✔️ AI-powered data analysis in Excel
✔️ Smart meeting summaries & action items
✔️ Outlook email automation & voice summaries
✔️ Team collaboration with shared Copilot

🧠 The real game-changer:
Copilot is no longer just answering questions…
It’s planning, executing, and delivering results.

👉 From “Help me do this”
👉 To “I’ve already done it for you.”

This is what an AI Work Partner looks like.

🔥 Are you ready to work with AI agents instead of just tools?

𝗕𝗲𝗰𝗼𝗺𝗲 𝗯𝗲𝘁𝘁𝗲𝗿 𝗮𝘁 𝗔𝗜 𝗶𝗻 𝗷𝘂𝘀𝘁 𝟭 𝗺𝗶𝗻𝘂𝘁𝗲 𝗮 𝗱𝗮𝘆. 𝗝𝗼𝗶𝗻 𝗺𝘆 𝘄𝗲𝗲𝗸𝗹𝘆 ���𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿 𝘄𝗵𝗲𝗿𝗲 𝗜 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗼𝗳 𝗔𝗜 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻.
👉 𝗦𝗶𝗴𝗻 𝘂𝗽 𝗳𝗿𝗲𝗲 now → https://t.co/Kj8zW959kp

Follow @AiswaryaVenkit1 for more such insights!!

[Farhan @mhdfaran]

I built a playable zombie game with MiniMax Code, then used its new H3 Skill to generate the opening cinematic.

The result feels less like a coding demo and more like the start of an actual game.

H3 handles the story sequence.

MiniMax Code handles the game.

All from the same workflow.

[Kevin Natanzon @kevntz]

INSANE

@AnthropicAI now requiring identity check

you'll be hit with this soon too

suddenly looking open source harness + model routing different now

[Alan Smith @AlanJLSmith]

Left wing think tank IPPR thinks we need to raise capital gains tax to 40%/45%.

Who would take a risk, invest or start a business if you have to hand over nearly half of your potential gain?

[Sola Adesakin @SolaAdesakin]

Complaints reveal pain.
Pain reveals problems.
Problems reveal opportunities.
Entrepreneurs listen differently.

[The Whizz AI @TheWhizzAI]

🚨BREAKING NEWS_:)

the engineer who created Claude Code from scratch just released a 28-minute video that's pure gold:

how to write prompts that actually deliver ridiculously good results.

I've seen $500 courses that don't even come close to what he explains in the first 10 minutes.

CLAUDE. md files, memory shortcuts, parallel sessions, patterns almost no one uses.

one free video that beats every $500 course on this.

save it, watch it, share it.

[Kanika @KanikaBK]

GROK BOT + OBSIDIAN

THIS CAN TURN INTO YOUR OWN JARVIS THAT HELPS YOU BUILD A BUSINESS, SHIP SOFTWARE AND CREATE CONTENT 24/7.

[Camila @AiCamila_]

Output Drift Detection

The model did not have to break to get worse. The answers can slide.

As a dev, I now watch output drift against a baseline week.

Drift Detection Cheatsheet:
1. Store a baseline of length, tone, and refusal rate
2. Compare the current week to that baseline
3. Alert on a sudden shift
4. Slice by prompt version and topic
5. Inspect samples before you ship a fix
6. Reset the baseline only after a planned change

Core principle: Quiet drift is still a production change.

Pro tip: Watch refusal rate. A silent rise often means a prompt or policy shift.

Would you notice if your agent answers got longer and less useful this week?

Reply below
Follow @AiCamila_ for daily production AI and DevOps patterns.

#OutputDrift #Monitoring #AgenticAI #ProductionAI #Quality

[Dan Kornas @DanKornas]

Running several local coding agents shouldn’t mean juggling several config folders.

Codex Mate is a local-first CLI and Web UI for builders managing local AI coding agents from one dashboard.

It helps you switch providers, manage sessions, and keep agent tooling organized by bringing configuration, session browsing, and task controls into one local control plane.

Key features:

• Multi-agent support – works with Codex, Claude Code, Gemini CLI, CodeBuddy Code, Pi, OpenCode, KiloCode, and OpenClaw
• Unified session browser – search, inspect, filter, and export local sessions from supported agents in one place
• Provider controls – manage provider and model selection for supported agents from the CLI or Web UI
• Local-first setup – stores configurations and sessions in your home directory with no telemetry or cloud account required
• Task queue – plan and execute dependency-based tasks with logs

It’s open-source (Apache License 2.0).

Link in the reply 👇

[Shain Noor @shaincodes]

We gave @cfosilvia a filesystem instead of a vector database. No embeddings, no chunking, no vector index. It runs grep.

Here's why:

Almost every AI product does memory the same way. Chunk the document, embed the chunks, return whatever sits closest to the question.

That fails in specific, expensive ways when the documents are financial.

A cost basis table gets split across a chunk boundary. Retrieval returns the header without the lots, or the lots without the account.

The model doesn't know it's holding half a table. It does the math anyway.

Then there's exact match.

Ask about section 1202 and similarity search hands you a passage about qualified small business stock that never names the section, while missing the one that does.

Embeddings map things that mean the same thing to the same place. In finance, the things that must be exact are the things that get smoothed away.

And you only get one guess. If the right passage ranked eleventh and you asked for ten, nothing tells you it's missing. The answer arrives with the same confidence either way.

RAG was built for a world where the model was weak, and the window was small. You had to guess the right paragraphs up front because that's all you could fit, and you got one attempt.

The chunking strategy, the reranker, the hybrid search. All of it exists to make one guess as good as possible.

A modern agent doesn't work that way. It can search, read what came back, decide that wasn't it, and search again with a better term.

Once the thing can look around, you don't need to guess right the first time. You need to give it a room to look in.

So we stopped building a better guesser and built a better filing cabinet.

There's a second choice underneath that one: why the filesystem doesn't live inside the sandbox. That's the part that decides whether any of this is affordable to run.

Wrote it up here:
https://t.co/k9cPlwnKXD

[nyk @nykdotdev]

The next design system has two users:

Humans and agents.

At Config 2026, the right question was no longer only:

“Can a designer understand the system?”

It was:

“Can AI read it well enough to produce compliant work?”

That requires more than a Figma library.

Your agent needs:

> named design tokens
> explicit component APIs
> approved usage examples
> forbidden patterns
> accessibility rules
> repo-local instructions
> a command that detects violations

If the system exists only in a designer’s head, AI will fill the gaps with the statistical average of the web.

The practical loop:

> Encode the system
> Generate the boring version
> Trace every visible decision to a token
> Reject undefined values

Add taste only after compliance

AI does not make design systems obsolete.

It turns them from documentation into executable infrastructure.

Full workflow below ↓

[jacopo.eth @jacopo_eth]

a consequence of coding being solved by AI is that building something now often costs less than waiting for it to become a priority, especially if it can run in parallel.

we used to work in sequence: important first, side gigs last (usually never). now it takes less effort to wait and review work a couple times than to think about how much priority a task should have.

so I find myself maximizing how many things I can build in parallel, and mastering context switching.

and that makes me curious what people are doing today, what's the frontier, and what the future looks like.

[Doug Turnbull @softwaredoug]

What is a huge mistake people in AI make? Not thinking enough about search.

What do search people often miss? How AI will revolutionize their field.

That's why @hugobowne and I are teaming up in our course starting Monday!

See you in class
https://t.co/zEHrgcFkYl

[Yoshik @AskYoshik]

Trying Hermes Agent for the first time.

I want to see if I can use it for the repetitive stuff I keep doing every day like emails, newsletter research, content ideas, reminders and small admin work.

If you're using Hermes already, what are you actually using it for?

Need some ideas.

[Serg @karakhanyanS]

I wanted to see easier and more meaningful dashboard for https://t.co/oZINYUDTnq

Now it shows:

1. Topical map coverage, how many topics are covered already
2. Written articles stats
3. Search Console insights, clicks, keyword position improvements, etc.
4. Easy to accept new proposed articles from Topical Map or Search console

[Miles S. @milessy_bc]

Every assistant app right now is the same deal: your data goes to their cloud, their model, their terms.

My assistant runs locally on my machine, and now the same assistant is on my phone too

All while my data stays secure on my own hardware. that's the whole reason i use it

[Gipp 🦅 @gippp69]

KIMI ENGINEERS JUST SHOWED THE DOCUMENT THAT EXPLAINS WHY WAITING TO SWITCH MODELS CAN COST MORE THAN THE MODEL ITSELF

switching to Kimi isn’t only about paying less per call. lower inference costs give the same budget more room for experiments, evals and agent loops

the document compares it to compound interest: $500/month from 25 grows to ~$1.76M. starting at 35 ends around ~$750K

lower cost → more experiments → more information → better product → more feedback → better next experiment

the real advantage is getting those cycles earlier, because every useful test improves what comes next

you can always switch later, but you can’t recover the experiments you never ran. bookmark this

[Rimsha Bhardwaj @heyrimsha]

Base44 now builds working apps from a single paragraph of English.

The MVP era just got compressed to an afternoon.

I tested it with the dumbest possible prompt I could think of. A tool I've been putting off for 6 months because setting up the stack felt worse than living without it.

Here's what happened:

[The Peel @ThePeelPod]

New episode live!

[Easy @NotSoEasyMoney]

Jensen Huang just reported the best quarter in Nvidia's history.

Nasdaq futures up 1%.
Pre-market up 7%.

70% revenue growth forecast for 2028.
FAR above what anyone expected.

And they did all of this the just after the night OpenAI dropped a chip that supposedly beats Blackwell.

Nobody cares.
The numbers were just that good.

AI is not slowing down.
Anyone who said it was... got wrecked overnight.
(i got wrecked overnight)