---
title: "Slides: The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI"
category: "slides"
video_id: "hVJOnuhFmTA"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

## Source Video
[The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI](https://www.youtube.com/watch?v=hVJOnuhFmTA)

## Relationship To World's Fair 2026
These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

## Related Scheduled Sessions
- No individual scheduled session mapping has been assigned yet; treat this as an event livestream deck.

## Extracted Slides
![[assets/slides/hVJOnuhFmTA/slide-003.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-003.html)
- AI slide classifier: `content_slide` confidence `0.99`
- Text source: advanced OCR `rapidocr-live/full`.
- OCR decision: ready — Dense multi-column code/UI slide; OCR will read it more reliably than direct transcription.

Slide text:

> 8088 8010 ；x86-64:bytes 0018 80001 6604 0068 0018 0011 000c push mov sub mov mov pop ret 868606868686 554889E54883 488B75F05DC3 EC20488B7DF8 0x01 rbp,rsp rbp rsp,8x26 rsi,[rbp-0x10] rdi,[rbp-0x8] rbp sFind Python files>18 sfind.-typef-name*py-size·k $grep-RInTO0O1wc-1 sSho top5by size s1s-Uhs（find.-name'.py） 5curl-shttps://api.exanple.com/\ sCount Tooos in those files 42 sFetch API andpretty-print -re-r--r-. -W-F--r-- -r-r---- -rw-r--r-. -r--r- （"id:2.name²:Linus}. （p.PT.） （"id":3.name²:Grace°） users?linit-31j0. sort-kS-hr|head-n5 8.0Kutils/i0.py 6.1K tests/test_api.py 18k Lib/parser.py 12xapi/elient.py Conditionals user. Variables timit100 Functions ifresp.status_code200: Loops for Item in data: Data (JSoN）Primitive itens-[] def fetch（url,timeout-5): else: "role":'adnin" "16°:123, "email:*adaexanple.con* resp·http.get（url,tineouttineout） return resp.json() raise Error(resp.text) ifiten["active"]: itens.append（iten) (NOsr） son Response Format Endpoint Method Auth Token Timeout(s) 10 https://api.example.com/v1/users GET Bearer Token JSON 'actiw':troe, "iit:100, upe,:olo, What would you like to build?.Stream large files.Validate emails Add type hints and deduplicatesrowsby asaJSONarray. Use csv.DictReader Sort by updated_at desc Write aPython function that parses a CSVfile, keeps themostrecent record byupdated_at, and returns theresult Requirements: Include a count summary email (case-insensitive), docstring
> Opcodes Shell Primitives Fields Open Language

![[assets/slides/hVJOnuhFmTA/slide-004.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-004.html)
- AI slide classifier: `diagram` confidence `0.97`
- Text source: agent_vision.

Slide text:

> Tell me what matters.
> JUST A STRAW INTO THE OCEAN.

![[assets/slides/hVJOnuhFmTA/slide-007.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-007.html)
- AI slide classifier: `content_slide` confidence `0.99`
- Text source: agent_vision.

Slide text:

> Because it shouldn't need us to anymore.
> It can ask a follow-up. It can clarify mid-thought.
> It can notice it's missing something and say so.
> It should be human conversational

![[assets/slides/hVJOnuhFmTA/slide-008.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-008.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: advanced OCR `rapidocr-live/border-trim/opencv-adaptive`.
- OCR decision: ready — Dense diagram with small labels and multiple panels; OCR will be more reliable than manual transcription.

Slide text:

> Batch Carried Forward
> Loom PunchCard Terminal Prompt
> LOOm 2 PUNCH CARD TERMINAL 4PROMPT
> 2111161111135111366051113s1013151 0G Canno G OJOB payrOKL GSUBHIT Job 31245 subaitted Anatyze Q2 sakes by region S and sumnarize top drivers.: Mew Chst
> encode pattem. run batch > encode program, submit batch enter command, wait package intent, submit!
> ENCODE / PACKAGE SUBMIT WaIt / PROCESS Output / result.
> New intelligence, old protocol.

![[assets/slides/hVJOnuhFmTA/slide-009.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-009.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: advanced OCR `rapidocr-live/border-trim/contrast`.
- OCR decision: ready — Chart labels and legend are small; OCR should recover them better than manual transcription.

Slide text:

> Expressive growth
> hgh
> the gap the thoss
> Punoh:cirds low Cormmandline GuImouse Touch LUMS
> Expressree ceding what you are nlowed to say
> Channelhowhebitspbysicalymove
> Inletaction protocol Who holds the tloor

![[assets/slides/hVJOnuhFmTA/slide-012.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-012.html)
- AI slide classifier: `content_slide` confidence `0.96`
- Text source: advanced OCR `rapidocr-live/left-72/opencv-adaptive`.
- OCR decision: ready — Product UI screenshot with small interface text; OCR is the safer capture path.

Slide text:

> Frontier Voice
> :tuguo 鲁
> You 2:18 PM:
> 8 When's the next Timberwolves game?
> : Fromtier Voice 2:18 PMi
> The next Minnesota Tmberwolves game bs
> I (Eabanos-
> rdoez: no,
> Hey. Ted, cane on'rt.
> Frontlor Yoico 2ig pM
> Sure, I'm here! Whet's on youu mnd?
> Mossoge Frontier Voico-.

![[assets/slides/hVJOnuhFmTA/slide-013.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-013.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: agent_vision.

Slide text:

> TL;DR
> - OpenAI is reportedly testing an unannounced bidirectional voice model called “GPT-Bidi-1.”
> - Code references and early user tests show that the model can speak, hear, and listen simultaneously, handling mid-sentence interruptions naturally.
> - The unannounced model has already started rolling out to a select group of app users, hinting at an official release window this week.

![[assets/slides/hVJOnuhFmTA/slide-014.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-014.html)
- AI slide classifier: `content_slide` confidence `0.96`
- Text source: advanced OCR `rapidocr-live/bright-screen/opencv-adaptive`.
- OCR decision: ready — Dense paragraph text and small embedded examples are better suited to OCR than manual transcription in this pass.

Slide text:

> Enriching PersonaPlex's output with non-verbal aspects creates an important qualitative
> difference relative to systems without this dimension: PersonaPlex now recreates some of
> NVIDIA. the same cues humans use to read Intent, emotions, or comprehension.
> A Examples
> NVIdIa ADlR The following examples showcase PersonaPlex's behavior across different scenarios. in
> all audio files, you can hear the user speaking in the left channel and PersonaPlex in the
> right channel (shown in green).
> Assistant
> 11 0:01 0:26
> engaging way. Prompt: You are a wise and friendly teacher. Answer questions or provide advice in a clear and
> In this example from FullDuplexBench's Interruption evaluation, PersonaPlex
> demonstrates general knowledge, interrupterability, and natural turn taking.
> Customer Service - Banking
> 0:00 stilif- 0:55
> Information: The customer's transactlon for S1,200 at Home Depot was declined. Verify Prompt: You work for First Ncuron Bank which is a bank and your name is Ssnni Virtanen.
> customer identity. The transaction was ffagged due to an unusual location (transaction attempted in Miami, FL: customer normally transacts in Seattle, WA).

![[assets/slides/hVJOnuhFmTA/slide-015.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-015.html)
- AI slide classifier: `content_slide` confidence `0.97`
- Text source: advanced OCR `rapidocr-live/full`.
- OCR decision: ready — Diagram slide with many small labels and multi-panel structure is OCR-suitable.

Slide text:

> Conversation is more than turn-taking
> Whatreal-time conversational Al has to understand
> 1.PARTICIPANTS 2.FLOW
> mm-hm
> Whoishere Who isspeaking Turn-taking Backchannels
> Whoislistening 3.MEANING Who isbeing addressed repair+social understanding Natural conversation= timing+context+ Interruptions&repair 4.ACTION Overlap Timing
> 口
> Attention Thread tracking
> Grounding Shared context 800 intentions Beliefs/ commitments Decisions/ Whento speak vswait

![[assets/slides/hVJOnuhFmTA/slide-016.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-016.html)
- AI slide classifier: `content_slide` confidence `0.94`
- Text source: advanced OCR `rapidocr-live/bright-screen/opencv-adaptive`.
- OCR decision: ready — Dense product UI screenshot with many small labels is OCR-suitable.

Slide text:

> O Produet roqurements revlew 1 Pauta (URaply)
> Listening
> Szhuhold euea. Prodvs - Lesd. Sem Broretrg Jordan chooerg rot to sp
> FT
> TAternoon, Sam. H Jorden.
> It joins like a teammate - and starts by listening.

![[assets/slides/hVJOnuhFmTA/slide-017.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-017.html)
- AI slide classifier: `content_slide` confidence `0.95`
- Text source: advanced OCR `rapidocr-live/border-trim/contrast`.
- OCR decision: ready — Dense product UI screenshot with small embedded text is OCR-suitable.

Slide text:

> Productrequlrementsrevlewe IPsuse UReplzy
> AI
> Presenting
> Sskeholoer Dana Product-Leod Sem Eogineering Jordan Suggested clarification
> QSHAREDBYAI Finance Controls Policy v3 Expense approvals exceeding S5,oo require second-level authorization-the reporting manager and a Finance spprover. 54.2-Approvalthresbods doaypwatoay COALS Hod
> O-wnichrequirement is this? REQ-142-expensacrvls
> What kind of requests, though? Resove approval scope
> Dara Expense approvalsfirst.Accessrequests eventually. asdwey
> Al,hold that. Sam
> Sam Actually-let'spause.Expense approvals,orageneral approvalworkfiow?
> Dana Expense approvals.Flrstrelease.
> Sam Access requests are future scope.
> Jordin That changos the data model.Good toknow.
> Al,pull that up for everyone. Sam
> Oh-Idforgotten thatwasarule. Sorduas Pulling up the source -- so the room sees it too.

![[assets/slides/hVJOnuhFmTA/slide-018.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-018.html)
- AI slide classifier: `content_slide` confidence `0.95`
- Text source: none.
- OCR decision: ready — Dense product UI screenshot with multiple small text regions is OCR-suitable.
![[assets/slides/hVJOnuhFmTA/slide-019.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-019.html)
- AI slide classifier: `content_slide` confidence `0.98`
- Text source: advanced OCR `rapidocr-live/border-trim/contrast`.
- OCR decision: ready — Dense product UI screenshot with small multi-column text.

Slide text:

> Product requlrements revlew Il Pause UReply
> CHAT
> Suskeholoer Dana Product-Lead Sem Eogineening Jordan SAM What'sour currentmedanappxoval time? 23days median right now,the targetis same-day. A
> Right-over the imit it routes to a second approver. Sam ogreg re.h'sfine DAV
> Agreed.Under five,one tap's fine. Dana GOALS
> Sam Worksforme. Okay -— agreed, Expense approvals, five-thousand threshold. Jerztsrs agree Expense spprovals-firstrelesse Resove opprovalsoope Qi-Wnichrequremene is thia? REQ-142pnp
> Sam Al,capture that for us. Dana Actually-make the threshold ten thousand,not five. cAChive REQ-142 Answered-aised to$10.0o0[Samconfrmed) Q-ls theS5,oo0threshold stie curreet？ 000
> Sam Yes. Want me toupdate the requirement to a ten-thousand threshold? A CUEIS frcanofication.Expens0sovers10,000rouAetosecond-leve approvalper Firstrelesse:managers can approve crreject pending erpense requests drectly requests are explicity outofscope. Approve /reject exponserequests from a notification
> Al-is thisroom free after the meeting? Let me check-the room looks free after this,but- A Jordan ODxpnsos oevS1o,o00requiresecond-fnwlapproval (manigirFinance) EmployeeIsnodfied of the declslon Decision is recorded in audt history OManagerreceves anodfication forapendng expense OManager canapprove crejectfromtenotilcation ACCEPTANCECRITERIA
> Sam Until three? It updates the spec -- live. Spts

![[assets/slides/hVJOnuhFmTA/slide-020.jpg]]

- Recreated text/layout view: [open HTML recreation](/assets/slide-recreations/slides/hVJOnuhFmTA/slide-020.html)
- AI slide classifier: `content_slide` confidence `0.99`
- Text source: agent_vision.

Slide text:

> Loops, Prompts, Agents...
> useful patterns — but still constraining the interface
> Loops: predefined flow; hard-coded steps
> Prompts: manual context; submit + repair
> Agents: delegated tasks; still shaped by old affordances
> Design for what is possible, not just what old interfaces allow.


### Hidden Non-Slide Evidence
- [`slide-001.jpg`](/assets/slides/hVJOnuhFmTA/slide-001.jpg) — `speaker_stage` confidence `0.98`; Speaker closeup, no presentation slide content visible.
- [`slide-002.jpg`](/assets/slides/hVJOnuhFmTA/slide-002.jpg) — `speaker_stage` confidence `0.95`; Speaker shot with overlay text, not a standalone slide.
- [`slide-005.jpg`](/assets/slides/hVJOnuhFmTA/slide-005.jpg) — `speaker_stage` confidence `0.97`; Speaker closeup with one-word overlay, not a standalone slide.
- [`slide-006.jpg`](/assets/slides/hVJOnuhFmTA/slide-006.jpg) — `demo_video` confidence `0.94`; Camera shot of a monitor during a demo, not a presentation slide.
- [`slide-010.jpg`](/assets/slides/hVJOnuhFmTA/slide-010.jpg) — `demo_video` confidence `0.99`; Video footage of a person at a desk, not a presentation slide.
- [`slide-011.jpg`](/assets/slides/hVJOnuhFmTA/slide-011.jpg) — `demo_video` confidence `0.96`; Blurred app/demo footage with only a tiny header, not a readable slide.
- [`slide-021.jpg`](/assets/slides/hVJOnuhFmTA/slide-021.jpg) — `speaker_stage` confidence `0.99`; speaker close-up, not a slide
- [`slide-022.jpg`](/assets/slides/hVJOnuhFmTA/slide-022.jpg) — `speaker_stage` confidence `0.99`; speaker close-up, not a slide

Classification audit: `raw/sources/slide-ai-classification/slides/hVJOnuhFmTA/audit.json`

## Slide-Derived Subjects To Review
Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.