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Every meeting-notes automation I've built has the same weak spot. It's not the words. It's the names.
The transcript says "I'll send the contract Friday." Cool. Who's "I"? Get that wrong and the workflow assigns the task to the wrong person, the CRM logs the customer's objection as the rep's, and nobody notices until Friday comes and goes.
That's the problem AirCaps is going after with A5S Async v1. Speech-to-text built to get who said what right, not just what was said.
And the lead isn't close. #1 of 15 on VoiceArena, an independent benchmark, where the next-best model makes 36% more errors. Across 5 public meeting benchmarks, the next best makes 40% more. The benchmark harness is open source too, so you can check the work yourself.
If you're building on speech APIs, there are 5 free hours to throw your messiest crosstalk recordings at it. Link in the reply.
Introducing A5S Async V1: the world's most accurate speech recognition model for speaker-attributed transcription.
#1 on VoiceArena, ahead of ElevenLabs, AssemblyAI, Deepgram, NVIDIA, Meta & more.
The next-best model makes 41% more errors across 5 public benchmarks.
And yes, every lab says they're #1. So we open-sourced our benchmark.
Try it now👇
10 GITHUB REPOS THAT CAN AUTOMATE THE BORING PARTS OF YOUR WORK
Imagine having workflows that run on their own, recover from failures, connect different apps, and handle background tasks without constant supervision.
You don't need to build everything from scratch.
Here are 10 open-source tools worth exploring:
1. n8n
Connect apps, APIs, and AI models through visual workflows, with custom code when needed.
github.com/n8n-io/n8n
2. Oxylabs Web API MCP
Give AI agents access to web search, extracted page content, and structured data.
github.com/oxylabs/web-api-m…
3. Activepieces
Build and self-host automated workflows with a visual, low-code interface.
github.com/activepieces/acti…
4. Kestra
Create scheduled and event-driven workflows using simple YAML configurations.
github.com/kestra-io/kestra
5. Temporal
Build durable workflows that can recover and continue even after failures.
github.com/temporalio/tempor…
6. Windmill
Turn Python, TypeScript, and Go scripts into workflows, APIs, and internal tools.
github.com/windmill-labs/win…
7. Trigger.dev
Run background jobs with retries, schedules, and long-running task support.
github.com/triggerdotdev/tri…
8. Inngest
Build event-driven functions with step-based execution and automatic retries.
github.com/inngest/inngest
9. Hatchet
Manage distributed background tasks and workflows with a Postgres-backed engine.
github.com/hatchet-dev/hatch…
10. Apache Airflow
Build, schedule, and monitor Python-based data pipelines.
github.com/apache/airflow
What can you automate?
→ Repetitive business tasks
→ API integrations
→ Background processing
→ Data pipelines
→ Scheduled reports
→ AI-powered workflows
The real productivity boost isn't doing tasks faster.
It's building systems that handle those tasks without you having to repeat them.
🔖 Bookmark these repositories for your next automation project.
10 GITHUB REPOS TO GIVE YOUR AI APP A VOICE
AI can already write, reason, and generate images.
But what happens when you give it the ability to listen, speak, and even create natural-sounding voices?
These 10 open-source projects are worth exploring if you're building voice-powered AI applications.
1. Whisper.cpp
Run speech recognition locally with an efficient C/C++ implementation of Whisper.
github.com/ggml-org/whisper.…
2. Kokoro
Generate natural-sounding speech using a lightweight text-to-speech model.
github.com/hexgrad/kokoro
3. F5-TTS
Create expressive AI-generated speech with modern text-to-speech technology.
github.com/SWivid/F5-TTS
4. Fish Speech
Explore multilingual speech generation and voice cloning capabilities.
github.com/fishaudio/fish-sp…
5. CosyVoice
Generate multilingual speech and experiment with zero-shot voice cloning.
github.com/FunAudioLLM/CosyV…
6. Oxylabs Web API MCP
Connect AI agents to web search and publicly available online information.
github.com/oxylabs/web-api-m…
7. OpenVoice
Experiment with instant voice cloning and control over voice characteristics.
github.com/myshell-ai/OpenVo…
8. WhisperX
Get accurate speech transcription, word-level timestamps, and speaker identification.
github.com/m-bain/whisperX
9. Coqui TTS
Explore different voice models and build custom text-to-speech applications.
github.com/coqui-ai/TTS
10. Qwen2-Audio
Build applications that understand audio and support voice-based interactions.
github.com/QwenLM/Qwen2-Audi…
What can you build with these?
→ AI voice assistants
→ Speech-to-text applications
→ Multilingual voice generators
→ Audio transcription tools
→ Voice-enabled AI agents
The exciting part is that voice AI is no longer limited to basic text-to-speech.
Developers can now experiment with systems that listen, understand, and respond naturally.
🔖 Bookmark these repositories for your next voice AI project.
WHAT IF YOUR AI COULD PLAN THE WORK, USE THE TOOLS, AND FINISH THE JOB?
That's the idea behind autonomous AI agents.
And you don't have to build the entire system from scratch.
These 10 open-source GitHub repos give you the building blocks to create agents that can reason, take action, access data, and collaborate:
1. smolagents
Build lightweight, tool-using AI agents with Python.
github.com/huggingface/smola…
2. Agno
Create agents and multi-agent systems with tools, memory, and knowledge.
github.com/agno-agi/agno
3. Letta
Build agents that retain context through persistent memory.
github.com/letta-ai/letta
4. Oxylabs Web API MCP
Give agents access to web search, live data, and website extraction.
github.com/oxylabs/web-api-m…
5. CAMEL
Build teams of AI agents that collaborate on complex tasks.
github.com/camel-ai/camel
6. Langroid
Develop multi-agent applications with tools and agent coordination.
github.com/langroid/langroid
7. Pydantic AI
Create reliable agents with structured outputs and tool calling.
github.com/pydantic/pydantic…
8. Microsoft AutoGen
Experiment with applications powered by collaborating AI agents.
github.com/microsoft/autogen
9. Semantic Kernel
Connect AI models with code, plugins, and external services.
github.com/microsoft/semanti…
10. MCP Use
Connect agents to MCP servers and reusable tool integrations.
github.com/mcp-use/mcp-use
From research assistants to multi-agent automation, these frameworks give you plenty of ways to experiment.
The next generation of AI apps won't just respond to instructions.
They'll turn instructions into completed tasks.
🔖 Bookmark these repos for your next agent project.
I've built a lot of automations. This one's just an email address.
Cc viktor@viktor.com on a thread and the work gets done in the thread. Not a reply drafter. Not a scheduling bot. An actual AI employee, free to start.
🤝 Paid partnership
Starting today, anyone with an email address can have their own AI employee. Free to start.
@viktor_com started in Slack. Now Viktor has an email address, so billions of people can reach it.
Just email viktor@viktor.com to get started.
Put Viktor on cc to book a meeting. Or forward any kind of work.
10 GITHUB REPOS TO KEEP YOUR AI APPLICATIONS RUNNING SMARTER
Building an AI application is one challenge.
Knowing when it fails, why it fails, how much it costs, and how to improve it is another.
These 10 open-source projects can help you monitor, test, evaluate, and manage AI applications in production.
1. Langfuse
Track LLM calls, prompts, token usage, costs, and performance in one place.
github.com/langfuse/langfuse
2. Arize Phoenix
Trace AI workflows, evaluate responses, and debug RAG pipelines.
github.com/Arize-ai/phoenix
3. Promptfoo
Test prompts across models, compare outputs, and catch performance regressions.
github.com/promptfoo/promptf…
4. DeepEval
Evaluate LLM applications with automated tests for hallucinations, response quality, and RAG performance.
github.com/confident-ai/deep…
5. TruLens
Measure retrieval relevance and check whether AI responses are grounded in the provided context.
github.com/truera/trulens
6. LiteLLM
Connect to 100+ LLM providers through one API with routing, fallbacks, and spend tracking.
github.com/BerriAI/litellm
7. Helicone
Monitor LLM requests, latency, costs, and usage through an observability layer.
github.com/Helicone/helicone
8. MLflow
Track experiments and manage tracing and evaluation for machine learning and LLM applications.
github.com/mlflow/mlflow
9. OpenLIT
Monitor LLM traces, metrics, and GPU usage with OpenTelemetry support.
github.com/openlit/openlit
10. Oxylabs Web API MCP
Connect AI applications and agents to live web data through a scraping API.
github.com/oxylabs/web-api-m…
Why should you care?
→ Catch issues before users report them.
→ Understand where your AI responses go wrong.
→ Track model usage and application costs.
→ Compare models and improve output quality.
→ Build more reliable AI systems.
Building an AI app is just the beginning.
The real goal is making it dependable in the real world.
🔖 Bookmark these repositories for your next AI project.
Your phone system is the dumbest tool in your stack.
Your CRM has AI. Your inbox has AI. Your docs have AI. And your phones are still a call log you scroll at 8 AM trying to remember who you forgot to call back.
Allo just fixed that for anyone running Grok Bot. Their official plugin is live in the Grok Bot marketplace, and it turns your business line into something you can just talk to.
Setup is almost insulting. Click add, sign in to Allo once, authorize. No API key, no webhook to babysit, no middleware. As someone who builds integrations for a living, that stung a little.
Ask "who should I call back first?" and it reads your calls, texts and AI receptionist notes, then hands you the names in order. Ask what a customer wanted and it pulls the actual line from the transcript, with the date.
Say "text her back" and it drafts the message from your Allo line. Then it shows you who it's for and what it says before anything goes out. Ask for a draft, you get a draft. Nothing sends itself.
It'll even set up your AI receptionist from the chat. Tell it what to handle, it writes the instructions, adds your website to what it knows, and turns it on.
Three commands do the heavy lifting. /allo-briefing for the day's volume and what needs attention. /allo-followups for the calls nobody closed. /allo-report for answer rate and each rep's numbers against last week. Make any of them a routine and Friday's numbers just show up.
Here's what I actually respect. Grok Bot can't place a call. It loads your Power Dialer queue and you press start. Call flow edits save as drafts you publish yourself. It asks before bulk tagging or killing the receptionist.
Read freely, act with permission, never let the bot dial your customers on its own. Most agent integrations get this backwards and hand the model the keys on day one.
It works on every Allo plan because it runs on the Allo MCP, which also plugs into Claude, Cursor and Codex. You're not betting your phone system on one AI vendor.
If your team still builds the weekly call report in a spreadsheet, that's a choice now.
withallo.com/go/leo
10 GITHUB REPOS THAT HELP AI UNDERSTAND EARTH FROM SPACE 🌍
What if AI could identify forests, detect buildings, map roads, and monitor environmental changes using satellite images?
That's already becoming possible with open-source geospatial AI.
Here are 10 GitHub projects worth exploring:
1. TorchGeo
Train deep learning models using satellite imagery and geospatial datasets.
github.com/torchgeo/torchgeo
2. Segment Anything
Identify and segment objects in images using AI-powered prompts.
github.com/facebookresearch/…
3. Clay
Explore foundation models designed for Earth observation and geospatial data.
github.com/Clay-foundation/m…
4. Prithvi
Use pretrained AI models for land mapping, flood analysis, and environmental research.
github.com/NASA-IMPACT/Prith…
5. SAMGeo
Apply prompt-based segmentation to satellite and aerial imagery.
github.com/opengeos/segment-…
6. eo-learn
Create workflows to process and analyze Earth-observation data.
github.com/sentinel-hub/eo-l…
7. Raster Vision
Build computer vision pipelines for detecting and classifying geographic features.
github.com/azavea/raster-vis…
8. DeepForest
Detect individual trees from aerial imagery using deep learning.
github.com/weecology/DeepFor…
9. Solaris
Develop geospatial computer vision workflows for object detection and segmentation.
github.com/CosmiQ/solaris
10. SpaceNet
Access satellite imagery datasets and benchmarks for mapping roads and buildings.
github.com/SpaceNetChallenge
Why does this matter?
→ Track deforestation and forest growth.
→ Monitor floods and environmental changes.
→ Map roads, buildings, and urban development.
→ Turn satellite imagery into useful geographic insights.
The exciting part is that developers and researchers can explore these capabilities without building everything from scratch.
AI isn't just looking at images anymore. It's helping us understand our planet.
Bookmark these repos for your next geospatial AI project.
MY AI EMPLOYEE IS OCTOBER'S EMPLOYEE OF THE MONTH. NOT FOR THE JOB I GAVE HIM. FOR THE ONE HE GAVE HIMSELF.
I build integrations for a living. I've run teams across four countries, and the work rarely broke while people were online. It broke at the handoff, when nobody was watching.
Viktor, our AI employee in Slack, has been watching since June.
His October file:
→ 46 workflows behind our order sync, mapped and checked every day
→ a vendor quietly moved our billing webhook from 1 retry to 4. It was in the map before I'd finished my coffee
→ the same vendor retires 2 endpoints on 19 November. 9 of our 46 workflows call them. The migration plan was on my desk three weeks early
→ 13 blockers taken to their owners before standup
→ about 15 hours a week handed back to me
Nobody asked him to watch the vendor. That's the part that wins the award.
The plan is still a plan. He proposes, I approve, and nothing touches production without me.
The award goes to whoever noticed first. This month, that wasn't me.
Hire @viktor_com for your team. Start free.
#AIemployee #Automation
Paid Partnership
🤝 Paid partnership
10 GITHUB REPOS TO BUILD YOUR OWN AI AGENTS
AI agents are becoming easier to build, but the framework you choose can make a huge difference.
Whether you need memory, tool calling, multi-agent collaboration, or workflow automation, these 10 open-source projects are worth exploring:
1. Agno
Build AI agents with tools, knowledge, and memory.
github.com/agno-agi/agno
2. CrewAI
Create teams of AI agents that collaborate on complex tasks.
github.com/crewAIInc/crewAI
3. Pydantic AI
Build structured, reliable, and type-safe AI applications.
github.com/pydantic/pydantic…
4. OpenAI Agents SDK
Create agent workflows with tools, handoffs, and guardrails.
github.com/openai/openai-age…
5. Semantic Kernel
Connect AI capabilities with your existing applications and services.
github.com/microsoft/semanti…
6. Letta
Build agents that can maintain long-term memory and learn from interactions.
github.com/letta-ai/letta
7. Qwen-Agent
Develop agents with tool calling, code execution, and RAG capabilities.
github.com/QwenLM/Qwen-Agent
8. n8n
Automate tasks by connecting AI models with hundreds of app integrations.
github.com/n8n-io/n8n
9. LiteLLM
Access 100+ LLM providers through a unified API.
github.com/BerriAI/litellm
10. Oxylabs Web API MCP
Give AI agents access to live web search results and website data.
github.com/oxylabs/web-api-m…
What can you build with these?
→ Research assistants
→ Autonomous workflows
→ Multi-agent systems
→ AI-powered business automation
→ Agents with persistent memory
You don't need to build every component from scratch.
Start with the right framework, experiment, and build something useful.
🔖 Save this list for your next AI agent project.
8 GITHUB REPOS TO LEVEL UP YOUR AI VIDEO CREATION WORKFLOW
Creating AI videos doesn't always mean starting with a blank prompt.
You can learn from existing projects, reuse creative ideas, explore animation styles, and understand how others build their videos.
Here are 8 GitHub repositories worth checking out:
1. Awesome Opus Videos
Discover AI-generated video examples alongside the prompts used to create them.
github.com/yihui-dev/awesome…
2. Lemo Opuscar
Explore a workflow for creating short films with Claude Code across 51 visual styles.
github.com/lemomo-ai/lemo-op…
3. pdoom-video
Study a locally rendered 4K60 karaoke music-video project.
github.com/mexicat/pdoom-vid…
4. PDoomVideo
Explore another implementation of the same music-video concept and compare its creative approach.
github.com/JohnHeibel/PDoomV…
5. mg-styles-15
Explore 15 motion graphics styles with examples, prompts, and source code.
github.com/Vincentwei1021/mg…
6. ClaudeAnimationBase
Experiment with hand-drawn cartoon animations and 31 character expressions.
github.com/JohnHeibel/Claude…
7. Awesome Claude Videos
Find a collection of video-generation examples and workflows built around Claude.
github.com/athemeroy/awesome…
8. Opus Video Prompts
Explore Chinese-language AI video examples and reusable prompt ideas.
github.com/joeseesun/opus-vi…
Here's a useful way to learn:
→ Pick a video you like.
→ Study the prompt behind it.
→ Explore the source code.
→ Experiment with your own style.
You don't have to figure everything out from scratch.
Sometimes, the best creative inspiration is already sitting on GitHub.
Bookmark these repos for your next AI video experiment.
Your ICP list isn't the problem. Your timing is.
A perfect-fit buyer three weeks early ignores you. Three weeks late, they've already signed with whoever showed up first.
@cleanailabs reads activity signals to flag which companies are in a transaction window right now, and it's building toward predicting who's about to enter one. That's how you become the first touch instead of the fourth.
Selling into manufacturing, legal, fintech, or insurance tech, where one well-timed call decides the deal? Book a demo.
🤝 Paid partnership
Building an AI research agent? Start with these 10 GitHub repos.
They help AI find credible sources, read research papers, extract information, and generate answers backed by evidence.
1. OpenAlex – Explore scholarly research data.
github.com/ourresearch/opena…
2. Open Deep Research – Build agents that conduct multi-step research.
github.com/langchain-ai/open…
3. PaperQA – Get answers from scientific papers with citations.
github.com/Future-House/pape…
4. GROBID – Extract structured information from research PDFs.
github.com/kermitt2/grobid
5. Semantic Scholar API – Access paper metadata and citation data.
github.com/allenai/s2-folks
6. Open Research Knowledge Graph – Turn research findings into structured knowledge.
orkg.org
7. arxiv.py – Search and track research papers from arXiv.
github.com/lukasschwab/arxiv…
8. Haystack – Build search, retrieval, and question-answering pipelines.
github.com/deepset-ai/haysta…
8. LlamaIndex – Connect LLMs to documents and external data.
github.com/run-llama/llama_i…
10. Oxylabs Web API MCP – Give research agents access to live web data.
github.com/oxylabs/web-api-m…
The real value of a research agent isn't just how well it writes.
It's how well it finds evidence, checks sources, and supports its answers.
Bookmark this list for your next AI project.
10 GitHub Repos Using AI to Turn Satellite Images Into Real-World Insights
What if you could identify forests, map roads, detect buildings, and monitor floods using nothing but satellite imagery and AI?
That's exactly what these open-source projects are helping developers and researchers do.
Here are 10 repositories worth exploring:
1. TorchGeo
A powerful toolkit for training deep learning models on geospatial data and satellite imagery.
github.com/torchgeo/torchgeo
2. Segment Anything
Use prompt-based segmentation to identify objects and regions in images.
github.com/facebookresearch/…
3. Clay
Explore foundation models built specifically for Earth observation and geospatial intelligence.
github.com/Clay-foundation/m…
4. Prithvi
NASA's geospatial AI models for applications like flood mapping, land cover analysis, and environmental monitoring.
github.com/NASA-IMPACT/Prith…
5. SAMGeo
Bring promptable image segmentation into satellite and geospatial analysis workflows.
github.com/opengeos/segment-…
6. eo-learn
Create reusable pipelines for processing satellite imagery and detecting changes across landscapes.
github.com/sentinel-hub/eo-l…
7. Raster Vision
Build computer vision pipelines for classifying images and detecting geographic features.
github.com/azavea/raster-vis…
8. DeepForest
Detect individual tree crowns from aerial imagery using deep learning.
github.com/weecology/DeepFor…
9. Solaris
Develop geospatial computer vision workflows for object detection and image segmentation.
github.com/CosmiQ/solaris
10. SpaceNet
Access satellite imagery datasets and benchmarks for mapping roads, buildings, and infrastructure.
github.com/SpaceNetChallenge
The exciting part?
These aren't just tools for looking at satellite pictures. They help turn raw imagery into useful information about our changing planet.
From tracking deforestation to understanding urban growth, the applications are enormous.
Save these repos. The next big AI breakthrough might come from looking down at Earth.
10 GitHub repos every AI developer should know before putting an AI app into production.
Building an AI application is one thing. Making sure it stays reliable, accurate, and cost-efficient is another.
These open-source tools help you understand what's happening behind the scenes:
1. Langfuse
Track LLM calls, prompts, performance, and costs.
github.com/langfuse/langfuse
2. Arize Phoenix
Trace AI workflows and debug retrieval problems.
github.com/Arize-ai/phoenix
3. Promptfoo
Test prompts, compare model outputs, and catch regressions.
github.com/promptfoo/promptf…
4. DeepEval
Evaluate LLM responses, hallucinations, and RAG performance.
github.com/confident-ai/deep…
5. TruLens
Check whether your RAG application retrieves relevant information and generates grounded answers.
github.com/truera/trulens
6. LiteLLM
Connect multiple LLM providers through one API with routing and spend tracking.
github.com/BerriAI/litellm
7. Helicone
Monitor LLM requests, latency, usage, and spending.
github.com/Helicone/helicone
8. MLflow
Track experiments and evaluate machine learning and LLM applications.
github.com/mlflow/mlflow
9. OpenLIT
Monitor LLM traces, metrics, and GPU usage with OpenTelemetry.
github.com/openlit/openlit
10. Oxylabs Web API MCP
Bring live web search and extracted data into AI workflows.
github.com/oxylabs/web-api-m…
A working AI app is just the beginning.
You also need to know when it gives poor answers, where it spends money, and what needs fixing.
That's what separates a quick AI prototype from a reliable product.
Save these repos before your next AI deployment. 🔖
Your AI agent can browse the internet. But can it actually use a website like a human?
Click buttons, fill forms, collect data, navigate pages, and complete tasks.
These 10 GitHub projects are worth exploring if you want to build agents that can interact with the web.
10 tools for smarter browser agents:
1. Playwright MCP
Let AI assistants control browsers, navigate pages, and interact with website elements.
github.com/microsoft/playwri…
2. Jina Reader
Convert webpages into clean, readable content for LLMs.
github.com/jina-ai/reader
3. Oxylabs Web API MCP
Bring web search, retrieval, and data extraction into AI workflows.
github.com/oxylabs/web-api-m…
4. BrowserGym
Build and evaluate agents on real browser-based tasks.
github.com/ServiceNow/Browse…
5. Cloudflare MCP Server
Connect AI assistants with Cloudflare services and developer tools.
github.com/cloudflare/mcp-se…
6. Agent Browser
Automate browser interactions through an agent-friendly command-line interface.
github.com/vercel-labs/agent…
7. Browserbase MCP
Give AI agents access to cloud browsers through MCP.
github.com/browserbase/mcp-s…
8. ScrapeGraphAI
Extract structured website data using natural-language instructions.
github.com/ScrapeGraphAI/Scr…
9. Apify Actors MCP
Connect AI assistants to automation and web data extraction tools.
github.com/apify/actors-mcp-…
10. Steel Browser
Explore browser infrastructure designed specifically for AI agents.
github.com/steel-dev/steel-b…
Imagine combining these capabilities to build:
→ Agents that research websites automatically
→ AI assistants that complete repetitive browser tasks
→ Automated data collection workflows
→ Agents that test websites and fill forms
The next generation of AI agents won't just read the internet.
They'll know how to interact with it.
Save these repos for your next AI project. 🔖
Your first video game doesn't need a big development studio.
It needs an idea, a little creativity, and the right tools.
GitHub has some incredible open-source game development projects that let you build everything from simple 2D games to immersive 3D worlds.
Here are 10 worth checking out:
1. Godot
Create complete 2D and 3D games with a powerful open-source engine.
github.com/godotengine/godot
2. GDevelop
Turn game ideas into playable experiences using visual logic instead of traditional coding.
github.com/4ian/GDevelop
3. Phaser
Build interactive browser games using JavaScript.
github.com/phaserjs/phaser
4. Bevy
Explore game development with Rust and a modern ECS architecture.
github.com/bevyengine/bevy
5. Three.js
Create interactive 3D worlds directly inside web browsers.
github.com/mrdoob/three.js
6. Babylon.js
Build immersive 3D experiences with a feature-rich web engine.
github.com/BabylonJS/Babylon…
7. LÖVE
Develop lightweight 2D games using Lua.
github.com/love2d/love
8. Ren'Py
Create story-driven games with choices, dialogue, and multiple endings.
github.com/renpy/renpy
9. Stride
Build 2D and 3D games using C# and a visual editor.
github.com/stride3d/stride
10. UPBGE
Create interactive 3D environments using a Blender-based workflow.
github.com/UPBGE/upbge
The best part?
You don't have to start with an expensive engine or a massive team.
Pick one tool, experiment with an idea, and build your first playable game.
Which engine would you choose for your first game? 🎮
















