AI Lab

An AI spent 64 hours designing proteins to target scorpion toxins. Then the real test began. Anthropic says an internal Claude research model generated 318,484 candidate designs. Researchers chose 211 to make and test; 17 met the team's binding criteria. A crucial distinction: binding to a toxin is NOT the same as neutralizing venom. No cell or animal efficacy tests were done. This is not an antivenom. The real story is the workflow: AI proposes at scale -> experts set criteria -> labs test physical samples -> results are shared. In science, the answer isn't what a model predicts. It's what survives an experiment. The same rule applies to business AI: measure outcomes, not how impressive a demo looks. Source: https://www.anthropic.com/research/claude-scorpion-toxin-binder-design #AIResearch #PracticalAI

The next AI coding breakthrough may be in software written before its users were born. OpenAI tested newer models on COBOL, Fortran and other underrepresented languages. In its COBOL migration benchmark, GPT-6.1 Sol reached 86.6% accuracy at low reasoning effort, versus 5.4% for GPT-5.6 Sol. At higher effort: 97.9%. A test score is not a green light to rewrite a bank's core system. Real software has hidden dependencies and business rules. Human review still matters. What can a company do today? 1. Choose one non-critical legacy module. 2. Capture its inputs, outputs and edge cases. 3. Write regression tests first. 4. Ask AI to explain or migrate it. 5. Compare results and review every change. The real opportunity: making the software we depend on easier to understand, test and maintain. Source: https://openai.com/index/low-resource-programming-languages/ #PracticalAI #LegacySoftware

AI WEEKLY | OCT 12-19 Four shifts worth watching: 1. OpenAI: ChatGPT Slides makes editable, collaborative decks. Rolling out to eligible Pro, Business and Enterprise users with Space. https://help.openai.com/en/articles/6825453-chatgpt-release-notes 2. Google: Gemini 4 Argon reaches the Gemini app for AI Pro/Ultra subscribers, with stronger complex-task and coding support. https://blog.google/innovation-and-ai/products/gemini-app/gemini-4-argon-availability/ 3. Meta: Muse Wonder launches to builders via Model API and Muse Code. Consumer rollout comes later. https://about.fb.com/news/2026/10/introducing-muse-wonder-models/ 4. NVIDIA: RTX Spark laptops ship with up to 128GB of unified memory for local AI models and agents. https://nvidianews.nvidia.com/news/nvidia-rtx-spark-pcs-available-today-a-new-beginning-for-windows-pcs The pattern: AI is moving from chat to editable work, multi-step tasks and local execution. #AIWeekly #PracticalAI

One bad review is not a trend. It can be a test plan. Say a customer writes: "My order arrived late and nobody told me." Is the problem delivery speed, missing updates or the promise made at checkout? Don't guess. Remove names and order details, then give the review to AI with this prompt: "Separate what the customer actually said from your interpretations. Give me three competing explanations for this complaint. For each, suggest one small test, the evidence I need and one measure to watch. Include what would disprove the explanation. Don't treat one review as proof of a pattern." You might test clearer delivery dates, proactive delay messages or a dispatch-process change. These solve different problems. Pick one test, compare results with your recent baseline and read the next reviews. AI helps frame the questions. Customers and data tell you which answer holds up. #PracticalAI #CustomerExperience #SmallBusiness

Your family photos may outlive the stories behind them. Pick one old photo and ask someone who remembers it. AI can suggest questions, not answers. Describe the photo to AI (or upload it with permission), then paste: "Don't guess names, dates, places or relationships. Give me eight open-ended questions for a relative who remembers this photo. Ask about who is there, what happened before and after, and what the picture cannot show. Separate what is visible from what we still need to ask." With permission, record the conversation. Then ask AI to turn the transcript into a one-page story using only what was said. Keep exact quotes in quotation marks and label anything uncertain as unknown. Let them correct the draft. Save it with the photo. One picture becomes more than a file. It becomes a memory someone can pass on. #PracticalAI #FamilyHistory #EverydayAI

Your fridge isn't empty. Your plan is. Before ordering food again, try a five-minute AI dinner challenge. List what you actually have (or use a photo with a vision-capable AI app). Add the number of people, your time limit and any dietary restrictions. Then paste: "Using only these ingredients: [list], plus these staples I confirm I have: [list], suggest three different dinners for [number] people in under [minutes] minutes. Use perishable items first. For each option, give quantities, four clear steps and a separate list of anything missing. Don't quietly add ingredients or equipment I didn't name." Example: eggs + tomatoes + spinach + half an onion + bread can become a tomato-egg skillet, a spinach omelet or tomato toast. Choose one, then ask AI to turn it into a 20-minute cooking timeline. Check food freshness and safe cooking yourself; a photo cannot tell AI whether something is safe to eat. #PracticalAI #EverydayAI #FoodWaste

The call you keep putting off? Practice it with AI first. Refund request. Difficult client. A change at work. The first sentence is often the hardest. Give AI five minutes to play the other person. Paste this: "I need to call [person/role] about [issue]. My goal is [specific outcome]. Facts: [3 short points]. Play the other person realistically, one turn at a time. Raise one plausible objection; invent no facts. Wait for my reply after each turn. When I type STOP, tell me: Was my ask clear? What should I say more simply? Give me one better opening and a two-sentence follow-up message." Try it twice. On the second run, speak your answers aloud. Then make the real call yourself. Keep names, account numbers and private documents out of the prompt. AI can help you rehearse; it cannot know how the other person will actually respond. #PracticalAI #Communication #AIWorkflow

Before reposting an AI quote, find the minute it was said. A short clip can make a cautious statement sound like a bold prediction. Auto-captions can miss a word that changes the meaning. Use AI to investigate, not to certify the quote: 1. Find the original video or interview, not just the repost. 2. Give AI the alleged quote and the original transcript. 3. Ask: "Find the timestamp and exact words. Flag missing qualifiers, changed numbers and anything that appears only in the repost. Label it exact quote, paraphrase or unsupported. Never invent a timestamp." 4. Play that part yourself, including the lines before and after it. No original source? Don't put quotation marks around an unverified claim. If you paraphrase, say so and link the source. The workflow is simple: source -> timestamp -> exact words -> context. The last step still needs a human. #PracticalAI #MediaLiteracy #ContentCreation

A familiar voice is not proof of identity. A caller sounds like someone you know and urgently asks for money, a login code or access. The voice could be cloned. Don't try to decide by sound alone. Agree on one rule at home and at work: hang up and call back using a number you already trust. 1. End the call. Don't use a number or link the caller gives you. 2. Call the person from your saved contacts. If they claim to represent an organization, use its verified contact details. 3. For work payments or access, follow your normal approval process. A convincing voice does not override it. Can't reach them? Pause and check with another trusted person. Don't send money or codes while you verify. The useful question is not "Does it sound like them?" It's "Did I verify through a separate channel?" FTC: https://consumer.ftc.gov/articles/scammers-use-fake-emergencies-steal-your-money FBI: https://www.ic3.gov/PSA/2024/PSA241203 #AISafety #PracticalAI

The expensive AI agent bug is a loop. A tool fails. The agent retries. Then retries again. More requests, no result. Before an agent runs unattended, give it hard limits: - maximum steps and tool calls per run - maximum retries after a failure - a time limit - a token or spend ceiling, where usage can be measured - a clear reason when the run stops Give Codex or Claude Code this task: "Add these limits in application code, not only in the prompt. When a limit is reached, stop making tool calls and return a short status report with the reason. Write a test with a tool that always fails and prove the run stops. Show me where each limit is configured." Set provider-side spending controls too, where available. A polite instruction to "keep costs low" is not a circuit breaker. The useful test is not only "does it work?" It's also "does it stop when it doesn't?" #AIAgents #PracticalAI #Automation

The sofa fits. The room doesn't. Before buying furniture, give AI more than a room photo. Measure the walls, doors and windows. Add the size of the sofa, the furniture you are keeping and what the room needs to do. Then try this: "Using only these measurements, suggest 3 layouts for [room]: one with more seating, one with more open space and one with a work corner. For each, give a rough top-down sketch, the walking route, door swings and possible collisions. List every assumption. Ask for any missing dimensions instead of inventing them." Choose a promising sketch, then check it with a tape measure. Open the doors. Walk the route. A generated image can help you imagine the room, but it cannot prove that everything fits. AI is useful for comparing options before you spend money. You still make the final measurement. #PracticalAI #HomeDesign #AIWorkflow

Your AI-built site passed the visual check. Now put the mouse away. On a test version of your site, press Tab. Can you reach the menu, main button and every form field in a sensible order? Can you always see where you are? Can you activate the button with a key? If a form fails, does the error tell you what to fix? If you get stuck, note the page, the key you pressed, what happened and what you expected. Then give that evidence to Codex or Claude Code: "Fix the keyboard problems in this user journey. Keep the current design. Make focus visible, let me reach and activate each control, and make form errors clear. Explain what you changed and give me exact steps to retest it. Do not claim the whole site is accessible." Run the journey again yourself, without a mouse. AI can help fix the issue; it cannot replace a real usability check. #PracticalAI #WebAccessibility #VibeCoding

Your AI-built website looks great. Can a stranger actually use it? The homepage loads. The buttons look polished. But the "Contact us" form may still lead nowhere. Before sharing your site, run a first-visitor test. Pick ONE real goal: send an enquiry, book a demo, or find a price. Give a browser-enabled AI agent the staging URL and test data, then paste this: "Act as a first-time visitor. Starting at [URL], try to [GOAL] using only what is visible on the page. Test on desktop and a phone-sized screen. Record each step and what happened. If you get stuck, capture a screenshot and give the exact steps to reproduce. List the issues in order of how much they block the goal. Do not make a real purchase or submit a production form; use test data only." Fix the biggest blocker first. Then repeat the same journey yourself on a real phone. A site isn't finished when AI says it looks good. It's finished when a visitor can complete the task. #PracticalAI #VibeCoding #WebsiteTesting

One translated word can change your offer. "Free trial" and "free plan" sound similar. To a customer, they mean different things. Before publishing a translated page, FAQ or support reply, check its meaning: 1. Give AI the original, target language, audience and terms to keep unchanged. 2. Translate it. Then open a fresh chat and paste BOTH versions. 3. Use this prompt: "Compare ORIGINAL and TRANSLATION line by line for [target language]. Find omissions, changed numbers or dates, lost negations, altered promises and phrases that may sound unnatural to [audience]. Quote the exact source and translated wording for each issue. Suggest a correction and explain why. Mark anything you cannot verify. Do not silently rewrite the whole text." Check prices, deadlines, links and calls to action yourself. For contracts, policies or major offers, ask a qualified human reviewer to approve the final version. The goal: same meaning, natural language, no surprise promises. #PracticalAI #Translation #AIWorkflow

Your video looks great. Mute it. What is it saying? Before publishing an AI explainer, try the sound-off test: 1. Save its first, middle and final frames. 2. Add the voiceover transcript and your one-sentence goal. 3. Give them to an AI chat that accepts images. Copy this prompt: "Review these three frames as a first-time viewer with no audio. For each, separate what is visible from what you infer. What topic, benefit and next action would you understand? Flag claims in the transcript that the frames do not show. Suggest one opening line and three on-screen captions, six words max each. Keep them faithful to the transcript. Flag text covered by app controls. Do not assess timing from stills." Then play the full clip on your phone with sound off. Check that the captions are readable and appear at the right moment. If the opening frame is vague, change the shot or its order. The three frames may tell a different story than the script. #PracticalAI #AIVideo #ContentCreation

You packed 12 things. Somehow, nothing goes together. Try an AI outfit plan before you zip the bag. 1. Photograph clothes and shoes you might take. Label each item A, B, C... 2. Add trip length, forecast, activities, dress codes and laundry access. 3. Upload them to an AI chat that accepts images. Copy this prompt: "Build a daily outfit plan using only the labeled items in my photos. Match each day to my activities and forecast. Reuse suitable pieces, account for laundry, and include one backup combination. Return a day-by-day table with item labels, a packing checklist and pieces I can leave at home. Ask about unclear items. Do not invent clothes or assume fabric, waterproofing or comfort from a photo. Flag gaps before suggesting anything to buy." Try the combinations on before packing. Check comfort and warmth yourself. Add underwear, toiletries, documents and chargers separately. One useful test: can you remove two items and still cover every day? #PracticalAI #AIWorkflow #Travel

That thing in your drawer could be your next AI project. The camera you stopped using. The spare monitor. The desk lamp you keep moving around. Try turning ONE item into a ready-to-post resale listing. 1. Take four photos: full item, model label, accessories and visible wear. Hide serial numbers and personal details. 2. Add what you tested, what is included and your asking price. 3. Upload everything to an AI chat that accepts images. Copy this prompt: "Draft a resale listing from these photos and my notes. Give me a clear title, short description, condition, included items and five likely buyer questions. Use only confirmed facts. Ask about missing details before drafting. Do not infer that it works from a photo, invent specifications or hide damage. Keep the tone natural." Check every claim. Use real photos that show the condition. Set the price using comparable sold listings where available. Small challenge: pick one thing you haven't used in six months. #PracticalAI #AIWorkflow

AI made it sound simple. Can you explain it without looking? Reading an answer can feel like learning. The real test comes when you need to use the idea yourself. Pick one topic you need this week: webhooks, customer churn, a new tool at work. Add a reliable source if the details matter. Copy this prompt: "Be my tutor for [topic]. First ask what I already know and what I need to do with it. Explain one small idea in plain English. Then ask me to explain it back in my own words. Wait for my answer. Point out one specific gap, give a counterexample, and let me try again. Finally, give me a realistic situation where I must apply the idea. If a fact is uncertain, say so." Try it with a webhook: can you explain what triggers it, what gets sent, and what happens if delivery fails? If you can solve a new example without reopening the chat, the idea is starting to stick. #AIWorkflow #LearningWithAI #PracticalAI

The family-size pack can cost more per serving. Package design makes comparison difficult: different weights, bundle counts, discounts and loyalty conditions. Photograph each product with its shelf label. Copy this prompt: “Compare these products using only visible information. Extract: product name, package quantity, unit, regular price, promotional price, promotion condition and currency. Convert every option to one comparable base: price per 100 g, 100 ml or item. Show the formula and calculation for every row. Keep loyalty or multi-buy prices separate from unconditional prices. Mark unreadable values VERIFY. Flag the lowest unit price, but do not claim it is the best product or make nutrition, quality or freshness assumptions.” Check the label and calculation yourself. Then consider what the table cannot decide: expiry date, storage space, waste and how much you will actually use. Cheapest package and cheapest unit are not the same thing. #AIWorkflow #SmartShopping #PracticalAI

Your utility bill went up. Your usage may not have. The cause may be consumption, a new rate, fixed fees, taxes or more billing days. Collect 6–12 months of bills. Remove names, addresses and account numbers before using AI. Copy this prompt: “From each bill extract: period, days, meter readings, consumption, unit rate, fixed fees, taxes and total. Build a monthly table with usage per day and cost per day. Separate usage changes from rate or fee changes. Compare each month with the previous bill and the same season when available. Cite file and page for every value. Mark unreadable fields VERIFY. Flag anomalies, but do not invent causes or savings. Finish with questions for the provider.” Check every number against the originals. Then add real context yourself: weather, occupancy, travel or a new appliance. The goal is not “use less.” It is knowing what actually changed. #AIWorkflow #SmartHome #PracticalAI