Andrew Bolis

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Andrew Bolis

Andrew Bolis

@AndrewBolis

AI & Marketing Consultant ๐Ÿ“ข Former CMO ๐Ÿ“’ Get My Free Guides: https://t.co/UjSQZDlQ3N ๐Ÿ“ง [email protected] โžก๏ธ Follow for AI & business growth tips

Chicago, IL, USA Katฤฑlฤฑm Haziran 2011
162 Takip Edilen293.2K Takipรงiler
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
Canva + 60 minutes a day + a laptop + an internet connection = $339 per day. Normally, I'd charge $89 for this killer guide, but today it's yours for FREE. Like + comment 'Canva' and I'll send you my proven guide for FREE. Must follow me to get DM. FREE for 48 hours only.
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
Canva + 60 minutes a day + a laptop + an internet connection = $339 per day. Normally, I'd charge $89 for this killer guide, but today it's yours for FREE. Like + comment 'Canva' and I'll send you my proven guide for FREE. Must follow me to get DM. FREE for 48 hours only.
Andrew Bolis tweet media
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Urooj
Urooj@Urooj978ยท
If Andrew Ng says the way we prompt has changed, you listen. ๐Ÿง  โ€‹Most people are still stuck in 2022. But in 2026, AI prompting is a completely different game. โ€‹In this video, @AndrewYNg breaks down: โ€‹Deep Research Mode: No more surface-level answers. โ€‹Massive Context: Feeding AI more than just simple text. โ€‹Reasoning Time: Why "thinking fast" isn't always better for AI. โ€‹From building websites to "intuition" under the hood, this is the masterclass we all need.
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@Damn_coder Useful contrast between passive scrolling and active learning
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D-Coder
D-Coder@Damn_coderยท
You can scroll Netflix for an hour. Or spend 2 hours learning how LLMs actually work at a level most AI employees never reach. This Stanford lecture is the clearest breakdown I've seen. Bookmark it now
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@nrqa__ Helpful starting point for Claude Code ecosystem tools
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Nelly;
Nelly;@nrqa__ยท
9 GitHub repos for Claude code that will 10x your next project: [saving these for later] 1. awesome claude code ๐Ÿ‘‰ github.com/hesreallyhim/aโ€ฆ 2. claude mem ๐Ÿ‘‰ github.com/thedotmack/claโ€ฆ 3. everything claude code ๐Ÿ‘‰ github.com/affaan-m/everyโ€ฆ 4. gsd (get shit done) ๐Ÿ‘‰ github.com/gsd-build/get-โ€ฆ 5. lightrag ๐Ÿ‘‰ github.com/hkuds/lightrag 6. n8n-mcp ๐Ÿ‘‰ github.com/czlonkowski/n8โ€ฆ 7. obsidian skills ๐Ÿ‘‰ github.com/kepano/obsidiaโ€ฆ 8. superpowers ๐Ÿ‘‰ github.com/obra/superpoweโ€ฆ 9. ui ux pro max ๐Ÿ‘‰ github.com/nextlevelbuildโ€ฆ
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Nelly;@nrqa__

this changes filmmaking completely you can generate full storyboards from a script and remix other creators' workflows in one click with @flickartHQ AI just turned months of pre-production into an afternoon full short film + workflow below:

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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@mhdfaran This could improve offline productivity for many users
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Farhan
Farhan@mhdfaranยท
Wispr flow but 100% local and 100% free link in comment
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@heyrobinai Interesting step toward automating 3D environment creation
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Robin Delta
Robin Delta@heyrobinaiยท
rip 3d designers someone built a free open-source Claude Code tool that takes one image and generates full 3D worlds: meshes, physics, lighting, audio. that's years of Blender tutorials, automated.
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@sharyph_ Helpful reminder that evals can catch hidden issues early
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Sharyph
Sharyph@sharyph_ยท
Your Claude skill stopped working 3 weeks ago. You just don't know it yet. Model updates break skills silently. No warning. Just slightly off outputs you blame on yourself. Skills 2.0 has a fix. Here's how evals catch regressions before they hit your real work ๐Ÿ‘‡ newsletter.thedigitalcreator.co/p/claude-code-โ€ฆ
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@EyeingAI Helpful concept especially for finishing tasks without constant guidance
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EyeingAI
EyeingAI@EyeingAIยท
Iโ€™m kind of tired of AI that only talks me through the work. At some point, the useful version is the one that can open the right thing, click through the boring parts & actually help finish it.. Bridge is the first real attempt at this.๐Ÿ‘‡
Bridge@bridge_surf

Today, Bridge officially begins testing. For a long time, AI has mostly been a place to chat. We think the next step is letting agents safely use your computer to finish real work. Bridge is our first step toward that. Join the test: bit.ly/4dkJeGn #AgenticAI #bridge

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Nathan Hirsch
Nathan Hirsch@itsnathanhirschยท
Most ad agencies don't have a methodology. They have a media buyer. That's the whole problem. Brian's team at Interlace runs the PACK Method. Performance Plan. Account Structure. Creative. KPIs. Without a methodology you're paying for the agency's mood that week. With one, every stage is trackable. Every business in the portfolio is built on boring systems. EcomBalance has a closing checklist. TrioSEO has a content process. Now Interlace brings the same to Shopify ads. Launch deal Monday. Reply "Shopify" for first access. P.S. Building a 10-business portfolio (6 down). Documenting everything at nathanhirsch(dot)com/newsletter.
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@Shruti_0810 This highlights growing interest in AI monetization ideas
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Shruti Codes
Shruti Codes@Shruti_0810ยท
Earn $500 a day, all you need is these three things: 1. A computer 2. Wi-Fi 3. Time Below are 10 Claude prompts that can help you earn $500 a day:
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@Parul_Gautam7 This challenge could advance multimodal speech systems significantly here
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Parul Gautam
Parul Gautam@Parul_Gautam7ยท
GPTโ€‘4o and Gemini Live sound smooth, but they still donโ€™t know when to shut up or yield. Real fullโ€‘duplex AI dies on turnโ€‘taking โ€“ especially in multiโ€‘dialect Chinese. Thatโ€™s exactly what the 2026 FinVolution Global Data Science Challenge solves. ๐ŸŽฏ Predict speech events from conversation audio history โ†’ low latency, no awkward pauses. ๐Ÿ† $43k prize pool + direct entry to NLPCC 2026 ๐Ÿ“… Reg: May 13 โ€“ June 16 If you build voice agents or multimodal systems, this is your real benchmark. ai.ppdai.com/mirror/show?chโ€ฆ #AI #LLM #SpeechAI #ConversationalAI #FullDuplex #MachineLearning #NLP #GPT4o
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@TawohAwa Great resource especially for beginners entering AI field
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Awa K. Penn
Awa K. Penn@TawohAwaยท
ANTHROPIC HAS ITS OWN AI ACADEMY. > Official courses. > Includes certificate. > Free, no payment required. I'm sharing the 7 most useful ones to get started today. Save it, you'll thank me later. ๐Ÿ‘‡
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@shushant_l Helpful reminder that data quality still matters a lot
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Shushant Lakhyani
Shushant Lakhyani@shushant_lยท
I'm sad to see most people are still sleeping on using AI for analysis. Here's a complete guide to use AI to get hours of analysis work done in minutes. ๐Ÿ“‚ ai analysis โ”ƒ โ”ฃ ๐Ÿ“‚ why this matters โ”ƒ โ”ฃ ๐Ÿ“‚ faster decision making โ”ƒ โ”ฃ ๐Ÿ“‚ hidden pattern detection โ”ƒ โ”ฃ ๐Ÿ“‚ forecasting accuracy โ”ƒ โ”ฃ ๐Ÿ“‚ operational efficiency โ”ƒ โ”— ๐Ÿ“‚ large scale data analysis โ”ƒ โ”ฃ ๐Ÿ“‚ descriptive analytics โ”ƒ โ”ฃ ๐Ÿ“‚ historical reports โ”ƒ โ”ฃ ๐Ÿ“‚ dashboards โ”ƒ โ”ฃ ๐Ÿ“‚ trend summaries โ”ƒ โ”ฃ ๐Ÿ“‚ data aggregation โ”ƒ โ”— ๐Ÿ“‚ basic business insights โ”ƒ โ”ฃ ๐Ÿ“‚ diagnostic analytics โ”ƒ โ”ฃ ๐Ÿ“‚ root cause analysis โ”ƒ โ”ฃ ๐Ÿ“‚ anomaly detection โ”ƒ โ”ฃ ๐Ÿ“‚ pattern investigation โ”ƒ โ”ฃ ๐Ÿ“‚ issue breakdowns โ”ƒ โ”— ๐Ÿ“‚ event correlation โ”ƒ โ”ฃ ๐Ÿ“‚ predictive analytics โ”ƒ โ”ฃ ๐Ÿ“‚ forecasting models โ”ƒ โ”ฃ ๐Ÿ“‚ risk prediction โ”ƒ โ”ฃ ๐Ÿ“‚ machine learning โ”ƒ โ”ฃ ๐Ÿ“‚ behavioral prediction โ”ƒ โ”— ๐Ÿ“‚ probability scoring โ”ƒ โ”ฃ ๐Ÿ“‚ prescriptive analytics โ”ƒ โ”ฃ ๐Ÿ“‚ action recommendations โ”ƒ โ”ฃ ๐Ÿ“‚ optimization strategies โ”ƒ โ”ฃ ๐Ÿ“‚ scenario simulation โ”ƒ โ”ฃ ๐Ÿ“‚ automated decisions โ”ƒ โ”— ๐Ÿ“‚ resource allocation โ”ƒ โ”ฃ ๐Ÿ“‚ define the problem โ”ƒ โ”ฃ ๐Ÿ“‚ business question โ”ƒ โ”ฃ ๐Ÿ“‚ success metrics โ”ƒ โ”ฃ ๐Ÿ“‚ analysis objective โ”ƒ โ”ฃ ๐Ÿ“‚ outcome clarity โ”ƒ โ”— ๐Ÿ“‚ decision criteria โ”ƒ โ”ฃ ๐Ÿ“‚ data preparation โ”ƒ โ”ฃ ๐Ÿ“‚ crm data โ”ƒ โ”ฃ ๐Ÿ“‚ spreadsheets โ”ƒ โ”ฃ ๐Ÿ“‚ databases โ”ƒ โ”ฃ ๐Ÿ“‚ data cleaning โ”ƒ โ”ฃ ๐Ÿ“‚ inconsistency checks โ”ƒ โ”— ๐Ÿ“‚ secure handling โ”ƒ โ”ฃ ๐Ÿ“‚ choose the right tools โ”ƒ โ”ฃ ๐Ÿ“‚ chatgpt advanced data analysis โ”ƒ โ”ฃ ๐Ÿ“‚ claude โ”ƒ โ”ฃ ๐Ÿ“‚ microsoft copilot โ”ƒ โ”ฃ ๐Ÿ“‚ google gemini โ”ƒ โ”ฃ ๐Ÿ“‚ julius ai โ”ƒ โ”— ๐Ÿ“‚ zerve โ”ƒ โ”ฃ ๐Ÿ“‚ prompting โ”ƒ โ”ฃ ๐Ÿ“‚ role based prompting โ”ƒ โ”ฃ ๐Ÿ“‚ context injection โ”ƒ โ”ฃ ๐Ÿ“‚ structured instructions โ”ƒ โ”ฃ ๐Ÿ“‚ reasoning requests โ”ƒ โ”ฃ ๐Ÿ“‚ follow up prompts โ”ƒ โ”— ๐Ÿ“‚ output formatting โ”ƒ โ”ฃ ๐Ÿ“‚ marketing analysis โ”ƒ โ”ฃ ๐Ÿ“‚ audience prediction โ”ƒ โ”ฃ ๐Ÿ“‚ campaign analysis โ”ƒ โ”ฃ ๐Ÿ“‚ attribution tracking โ”ƒ โ”ฃ ๐Ÿ“‚ segmentation โ”ƒ โ”— ๐Ÿ“‚ conversion insights โ”ƒ โ”ฃ ๐Ÿ“‚ finance analysis โ”ƒ โ”ฃ ๐Ÿ“‚ fraud detection โ”ƒ โ”ฃ ๐Ÿ“‚ revenue forecasting โ”ƒ โ”ฃ ๐Ÿ“‚ expense tracking โ”ƒ โ”ฃ ๐Ÿ“‚ financial modeling โ”ƒ โ”— ๐Ÿ“‚ risk scoring โ”ƒ โ”ฃ ๐Ÿ“‚ healthcare analysis โ”ƒ โ”ฃ ๐Ÿ“‚ patient prediction โ”ƒ โ”ฃ ๐Ÿ“‚ anomaly alerts โ”ƒ โ”ฃ ๐Ÿ“‚ clinical insights โ”ƒ โ”ฃ ๐Ÿ“‚ treatment optimization โ”ƒ โ”— ๐Ÿ“‚ operational monitoring โ”ƒ โ”ฃ ๐Ÿ“‚ retail analysis โ”ƒ โ”ฃ ๐Ÿ“‚ inventory forecasting โ”ƒ โ”ฃ ๐Ÿ“‚ pricing optimization โ”ƒ โ”ฃ ๐Ÿ“‚ customer behavior โ”ƒ โ”ฃ ๐Ÿ“‚ demand prediction โ”ƒ โ”— ๐Ÿ“‚ competitor tracking โ”ƒ โ”ฃ ๐Ÿ“‚ logistics analysis โ”ƒ โ”ฃ ๐Ÿ“‚ route optimization โ”ƒ โ”ฃ ๐Ÿ“‚ downtime prediction โ”ƒ โ”ฃ ๐Ÿ“‚ supply chain tracking โ”ƒ โ”ฃ ๐Ÿ“‚ delivery forecasting โ”ƒ โ”— ๐Ÿ“‚ operational efficiency โ”ƒ โ”ฃ ๐Ÿ“‚ hr analysis โ”ƒ โ”ฃ ๐Ÿ“‚ attrition prediction โ”ƒ โ”ฃ ๐Ÿ“‚ workforce analytics โ”ƒ โ”ฃ ๐Ÿ“‚ engagement tracking โ”ƒ โ”ฃ ๐Ÿ“‚ hiring insights โ”ƒ โ”— ๐Ÿ“‚ productivity analysis โ”ƒ โ”ฃ ๐Ÿ“‚ common mistakes โ”ƒ โ”ฃ ๐Ÿ“‚ trusting ai blindly โ”ƒ โ”ฃ ๐Ÿ“‚ vague prompting โ”ƒ โ”ฃ ๐Ÿ“‚ poor quality data โ”ƒ โ”ฃ ๐Ÿ“‚ no human review โ”ƒ โ”ฃ ๐Ÿ“‚ skipping validation โ”ƒ โ”— ๐Ÿ“‚ confusing correlation with causation โ”ƒ โ”ฃ ๐Ÿ“‚ future of ai analysis โ”ƒ โ”ฃ ๐Ÿ“‚ autonomous analytics โ”ƒ โ”ฃ ๐Ÿ“‚ multimodal analysis โ”ƒ โ”ฃ ๐Ÿ“‚ agentic workflows โ”ƒ โ”ฃ ๐Ÿ“‚ real time intelligence โ”ƒ โ”— ๐Ÿ“‚ continuous monitoring โ”ƒ โ”— ๐Ÿ“‚ harsh truth โ”ฃ ๐Ÿ“‚ ai is not magic โ”ฃ ๐Ÿ“‚ prompts matter โ”ฃ ๐Ÿ“‚ data quality matters โ”ฃ ๐Ÿ“‚ human judgment wins โ”— ๐Ÿ“‚ speed + intelligence = advantage
Shushant Lakhyani tweet media
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@JaynitMakwana This could significantly improve agent level data retrieval systems
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Jaynit Makwana
Jaynit Makwana@JaynitMakwanaยท
๐Ÿšจ AI agent builders are shaking right now CatchAll just dropped the most powerful web data engine of 2026. It scans 2B+ pages & turns messy open web data into clean, struct. JSON datasets, so your agents finally see the events hidden beyond page one. Here is the breakdown๐Ÿงต:
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Andrew Bolis
Andrew Bolis@AndrewBolisยท
@HeyAmit_ Great reminder that fundamentals still drive high paying roles
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Amit
Amit@HeyAmit_ยท
Jane Street pays $750k/ year for quants who can answer how to use Stochastic Process and Markov Chains in quant trading. This 1-hour MIT lecture on probability gives you the same insights quants get paid $60K/month for. Bookmark & watch today.
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Muhammad Ayan
Muhammad Ayan@socialwithaayanยท
> be Andrew Feldman > sell first company SeaMicro to AMD > can't survive inside a big company > "immense ambition and a heart full of disobedience" > meet with an investor 6-7 times over 18 months > realize GPUs are just battlefield promotions of graphics chips > decide to build a wafer-scale chip the size of a dinner plate > something nobody has done in 75 years > first wafer self-destructs on power-up > back in the lab next morning > investor literally threatens to climb his fence to give him a term sheet > 10 years later > rings the bell at NASDAQ from a coffee shop in Portola Valley to a generational AI company. this is what conviction looks like.
Steve Vassallo@vassallo

In April 2016, I threatened to climb over @andrewdfeldman's fence to give him his first term sheet for @cerebras. It was April Foolโ€™s day, but I wasnโ€™t fooling around. The story started in October 2007, when Andrew and his co-founder Gary Lauterbach had just started SeaMicro. Even then, Andrew was a force of nature. He was extremely intense and miswired in all the right ways. You could feel the sparks flying off him. We didn't invest in SeaMicro, but we stayed in touch. Andrew and the team built SeaMicro then sold it to AMD in 2012. When AMD acquired SeaMicro, I had a hunch Andrew wouldn't last long inside a big company. He has, as I've said many times, immense ambition and a heart full of disobedience. By early 2014, he was looking for an escape hatch. Over the next year and a half, Andrew and I met 6 or 7 times. Sometimes in our office. Sometimes at a coffee shop in Portola Valley. Sometimes at our local tennis and swim club. We kept coming back to one thing: deep learning workloads were growing exponentially, and traditional compute architectures couldn't keep up. GPUs had become the default for neural network training, mainly because researchers had accidentally discovered they were less terrible than CPUs. Andrew, Gary and Sean saw the GPU for what it was: a battlefield promotion of a chip optimized for graphics. Better than a CPU, but not what anyone would design starting from a blank sheet of paper. Their key insight was that memory bandwidth, not raw compute, was the real constraint on what neural networks could achieve. So Andrew, Sean Lie, Gary Lauterbach, Jean-Philippe Fricker and Michael James set out to do something nobody had pulled off in the 75-year history of semiconductors: Build a wafer-scale chip the size of a dinner plate. In April 2016, I asked Andrew if we could be his first term sheet. @ericvishria at Benchmark and I co-led the round along with Pierre Lamond from Eclipse. Then the hard work began. In the 75-year history of computing, no one had made wafer scale work. Which meant no one had ever had to solve the problems that came from trying. How do you power a chip that large? How do you cool one? How do you maintain electrical continuity across tens of thousands of connection points on a single piece of silicon? To get there, Cerebras had to invent in nearly every modern computing discipline at once: semiconductors, systems, data fabric, software, algorithms. Each was a startup in its own right. Their first wafer self-destructed on initial power-up and Andrew and the team were back in the lab the next morning, identifying what didnโ€™t work and coming up with approaches to solving it. Yesterday, Cerebras went public. 19 years after our first meeting, 10 years after that April Fool's term sheet, theyโ€™ve built a generational AI company. From a coffee shop in Portola Valley to ringing the bell at the NASDAQ. What a journey. Proud to have been Andrew's first partner in Cerebras. Even prouder to call him my friend.

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