🏎️ The AI Race Just Got Intense (And How to Actually Keep Up)

Hey, it's Oliver, here's your AI update for this week!

In today's issue:

• Superhuman: The AI email app that users call "the perfect subscription I'd never cancel"
• Claude Opus 4.5 crushes coding benchmarks (80.9% on SWE-bench Verified)
• Use "Few-Shot" prompting to teach AI by example (10x better results)
• Build AI workflow chains that automate multi-step processes
• And more...

🛠️ Tool of the Week: Superhuman ($30/month) (Not Sponsored)

What it is:

An AI-powered email client that makes you get through your inbox twice as fast. It's Gmail or Outlook, but rebuilt from scratch with speed and AI at the core.

Why it matters now:

Here's the thing about Superhuman: it costs $30/month, and people absolutely refuse to cancel it. Users say things like "the perfect subscription I'd never cancel" and "I can't live without it."

I was skeptical too—who pays $30/month for email? But Superhuman just got a massive AI update (December 2025) with features that are genuinely different from other email tools.

Three ways it saves hours every week:

• Auto Labels + Auto Archive = Inbox Zero automatically – AI categorizes every email: "Response Needed," "Waiting On," "Marketing," "Cold Pitches." Create custom labels with prompts like "job applications" or "urgent requests." Turn on Auto Archive and marketing emails disappear automatically. Users clear hundreds of emails per day without thinking about it.
• AI writes in YOUR voice, not GPT's – The "Write with AI" feature learns your style by analyzing emails you've sent. It pulls from your calendar, past emails, and web research. The result sounds like you—people say "doesn't sound GPT-y at all" because it adapts tone per recipient.
• Ask AI knows your entire inbox – Press "?" and ask "What's the status of the Q4 budget?" It searches all emails and summarizes. Draft emails, schedule meetings, get answers—no digging through your inbox. Chat history saves so you don't re-ask questions.

Just launched (December 2025):

• Auto Drafts write follow-ups without prompting
• Smart reminders surface emails if people don't respond
• AI connects your inbox, calendar, and web research

The catch:

$30/month for individuals, $40/month for Business plan (includes CRM). But users save 4+ hours per week and respond 12 hours faster.

Real talk:

For people with 50+ emails/day where email is central to their job. If you get 10 emails a day, skip it. But if you live in your inbox? Users process email 2x faster.

Pricing:

Individual: $30/month | Business: $40/month

Bottom line:

The price is jarring until you realize it saves 4+ hours weekly. That's worth way more than $30 for most professionals. If email is 25%+ of your job, try it for a month.

Try Superhuman Free

🤖 1. Anthropic's Claude Opus 4.5 Sets New Coding Record (And It's 3x Cheaper Than Before)

Why This Matters

On November 24, Anthropic launched Claude Opus 4.5 with a specific claim: "best model in the world for coding, agents, and computer use." The benchmarks actually back it up.

• 80.9% on SWE-bench Verified (beats Google's Gemini 3 Pro at 76.2% and OpenAI's GPT-5.1 at 77.9%)
• 66.3% on OSWorld (computer use benchmark, best in class)
• $5/$25 per million tokens (down from $15/$75 for the previous Opus 4)

This is the first model to break 80% on SWE-bench Verified, which tests whether AI can autonomously solve real GitHub issues—fixing bugs, adding features, refactoring code. That's not trivial code completion, that's actual software engineering.

What Changed

Opus 4.5 doesn't just autocomplete or suggest fixes—it plans multi-step solutions, coordinates changes across multiple files, and handles ambiguity without constant handholding. Early testers report it can complete tasks that Sonnet 4.5 couldn't even attempt.

The pricing drop is massive: $5 input / $25 output versus the old $15 / $75. That makes Opus-level intelligence actually affordable for production use, not just occasional experiments.

Anthropic gave Opus 4.5 the same coding test they give prospective performance engineering candidates. The AI outperformed most human applicants. That's not a benchmark gaming trick— that's a real-world signal that AI coding has crossed a new threshold.

Real-World Applications

• GitHub Copilot integrated it immediately as the default agent model for users on Business and Enterprise plans
• Cursor, Warp, and other AI coding tools upgraded within days
• Lovable, a no-code platform, reported that Opus 4.5's reasoning depth "transforms planning" for code generation

The practical impact: developers are using it for multi-hour autonomous coding sessions, complex refactors that span dozens of files, and architectural decisions that require understanding trade-offs.

Bottom line:

The gap between "AI can help with code" and "AI can write production code autonomously" just got a lot smaller. This isn't replacing developers yet, but it's replacing a lot of the grunt work— and doing it faster and cleaner than most humans can.

🧨 2. OpenAI Declares "Code Red" and Fast-Tracks GPT‑5.2 to Fight Back

The Situation

On December 2, OpenAI CEO Sam Altman issued an internal "code red" directive. The reason: Google's Gemini 3 topped the leaderboards last month, and Anthropic's Claude Opus 4.5 followed immediately after. OpenAI is now scrambling to respond.

What's Happening

• GPT‑5.2 release moved up to December 9 (originally scheduled for later this month)
• All “side projects” paused including advertising tests, shopping agents, and experimental features
• Internal focus shifted to core model quality over new product features
• Developer memo warned of “various errors during December” as infrastructure gets rebuilt at speed

Sources report that GPT‑5.2’s internal benchmarks edge out Gemini 3 on reasoning tasks, but that's unconfirmed. What’s clear: OpenAI is treating this as an existential challenge, not a routine release.

The Competitive Context

ChatGPT’s market share is slipping:

• Over the last four months, ChatGPT’s share of AI chat app users dropped 3 percentage points
• Gemini gained 3 points and users’ daily time doubled to ~11 minutes
• ChatGPT’s daily time per user increased only 6% and actually declined in November
• Perplexity and Claude posted triple‑digit year‑over‑year growth

This isn't about benchmarks anymore—it's about whether ChatGPT can maintain its position as the default AI assistant. Google has distribution through Search and Android. Anthropic has enterprise contracts. OpenAI has brand recognition, but that’s not enough if competitors catch up on quality.

What GPT‑5.2 Will Focus On

Reports say the update prioritizes “speed, reliability, and customizability” rather than flashy new features. OpenAI wants to close the gap Google created with Gemini 3 while preserving ChatGPT’s ease of use.

The “code red” framing matters: it signals a shift from long‑term strategic planning to rapid‑response execution. This is the AI industry moving from multi‑month release cycles to continuous competitive sprints.

Bottom line:

The AI race is accelerating. OpenAI, Google, and Anthropic are all releasing major updates within weeks of each other, not months. For users, this means better models faster— but it also means more fragmentation and constant learning curves as tools rapidly evolve.

1. 📚 Few‑Shot Prompting: Teach AI By Example (Not By Explanation)

The technique: Instead of describing what you want in words, show AI 2–3 examples of the exact output format you need. AI learns the pattern and replicates it.

Why it works: AI is better at pattern matching than following abstract instructions. Examples eliminate ambiguity—AI sees exactly what “good” looks like.

Copy‑paste template:

Here are 3 examples of the format I need:

Example 1:
Input: [sample input 1]
Output: [desired output 1]

Example 2:
Input: [sample input 2]
Output: [desired output 2]

Example 3:
Input: [sample input 3]
Output: [desired output 3]

Now apply this same format to:
Input: [your actual input]
  

Example – Email Tone Matching:

Example 1:
Input: Reject a meeting request
Output: "Hey Sarah, thanks for reaching out! I'm slammed this week, but I'd love to connect. How's next Tuesday at 2pm?"

Example 2:
Input: Request a deadline extension
Output: "Hi Mike, quick heads up—I'm running a day behind on the Q4 report. Could we push to Friday? Happy to share a draft Thursday if helpful."

Now write in the same style:
Input: Thank a colleague for covering your shift
  

AI will match the casual‑but‑professional tone automatically.

When to use: Specific tone requirements, data formatting, structured outputs, maintaining consistent style.

Tools:ChatGPT | Claude | Gemini

🔗 2. Chain-of-Thought + Tool Use: Build AI Workflow Chains

The technique: Break complex tasks into a sequence of AI-powered steps where each output feeds into the next input. Like an assembly line for AI operations.

Why it works: AI excels at individual tasks but struggles with complex multi-step processes. Chaining steps together maintains quality at each stage while automating the entire workflow.

Copy-paste template:

Complete this workflow in steps:

Step 1: [First task]
Output labeled as "STEP 1 OUTPUT:"

Step 2: Use STEP 1 OUTPUT to [second task]
Output as "STEP 2 OUTPUT:"

Step 3: Use STEP 2 OUTPUT to [final task]

[Provide initial input]
  

Example - Content Repurposing Chain:

Transform this blog post into social media content:

Step 1: Extract the 3 most important insights
Output as "KEY INSIGHTS:"

Step 2: Using KEY INSIGHTS, write 3 LinkedIn posts (150 words each)
Output as "LINKEDIN POSTS:"

Step 3: Using KEY INSIGHTS, write 3 Twitter threads (5 tweets each)
Output as "TWITTER THREADS:"

Blog post: [paste content]
  

Each step builds on the previous output, ensuring consistency across formats.

Example - Research to Report:

Step 1: Find 5 recent articles about [topic] and list key findings
Output as "RESEARCH FINDINGS:"

Step 2: Using RESEARCH FINDINGS, identify 3 main trends
Output as "KEY TRENDS:"

Step 3: For each trend, write 2-3 sentences on business implications
Output as "EXECUTIVE SUMMARY:"

Topic: [your topic]
  

Power move: Save successful chains as templates you can reuse with different inputs.

When to use: Content repurposing, research synthesis, multi-step analysis, any workflow where each stage matters.

Tools:ChatGPT | Claude (best for long contexts) | Gemini

3. 🧠 Context Window Hacking: Make AI Remember 10x More

The technique: Use strategic summarization and context compression to make AI work with much more information than its context window technically allows.

Why it works: Modern AI has huge context windows (200K+ tokens), but quality degrades past a certain point. Intelligent compression gets better results than dumping everything in.

Copy-paste template:

I'm providing information in chunks. For each chunk:
1. Read and understand
2. Summarize key points in 2-3 bullets
3. Wait for next chunk

After all chunks, I'll ask you to use all summarized information.

Chunk 1: [First section]
  

Example - Processing Multiple Documents:

I have 5 research papers. For each, I'll paste the abstract and conclusion.

Extract for each:
- Main finding (1 sentence)
- Methodology (1 sentence)
- Key limitation (1 sentence)

Store as PAPER 1, PAPER 2, etc.

After all 5, create a comparison table.

Paper 1: [paste]
  

Example - Long Conversation Memory:

When a conversation gets too long, compress it:

Before we continue, create a "memory summary":
- 5 main points we've agreed on
- 3 open questions still being explored
- Any specific examples we referenced

Then continue using this as foundation.
  

Power move - Progressive detail:

Start broad, then zoom in:

Round 1: Give 10,000-foot overview in 3 sentences
Round 2: Expand to 10 bullet points
Round 3: For bullets 2, 5, and 7, give detailed examples

This controls depth without overwhelming context.
  

When to use: Long documents, multiple sources, ongoing projects, research synthesis.

When NOT to use: When you need verbatim quotes, legal/compliance work, when nuance matters more than summaries.

Tools:ChatGPT | Claude (200K tokens) | Gemini

🔗 Useful Links:

• Claude Opus 4.5 Announcement | Model Card
• Superhuman | AI Features
• SWE-bench Verified Leaderboard

📚 More Resources:

• ChatGPT | API Docs
• Claude | Developer Console
• Gemini | AI Studio

A quick note before you go

Thanks for reading this week’s Brain Bytes — I hope something here helped you move faster or think better.

How’d this one land?

• A ✨ Super Helpful!
• B 🤔 Some Good Stuff!
• C 😕 Could be better.

See you next week, — Oliver