Of course. As an experienced business consultant, I can help you structure this expert roundtable to produce a clear, data-driven investment thesis. Your pre-research has been thorough, providing an excellent foundation.

This problem is a classic case of Forecasting and Risk Assessment under uncertainty. Your client, a general investor, needs a recommendation that is not just a guess, but a conclusion derived from a structured analysis of conflicting evidence.

The goal is to move beyond the surface-level market odds and generate a fundamental probability for each timeline. This will allow you to identify potential mispricing and make an informed investment decision. The final output should be a concise investment thesis outlining the recommended position, the core reasoning, and the key events to monitor.

Here is a comprehensive research proposal designed to achieve that goal.

Business Research Proposal: Tesla FSD Launch Timeline Analysis

This plan is divided into two core parts: Information Collection, which focuses on gathering expert opinions in a structured manner, and Information Analysis, which details how to convert that discussion into an actionable investment strategy.

Part 1: Information Collection Plan

The information collection phase will use the frameworks you've selected: Multi-Criteria Weighted Scoring to quantify expert opinions and Scenario Pathway Analysis to build a qualitative narrative.

Recommended Frameworks & Applicability

• Multi-Criteria Weighted Scoring: This is a decision-making tool that breaks a complex question into smaller, evaluable components. Each component (or "criterion") is assigned a weight based on its importance. For this problem, it allows you to systematically assess the FSD launch probability by separating the key drivers—regulation, technology, definition, and credibility—and weighting them according to the provided structure (e.g., Regulatory at 40%). This transforms a qualitative debate into a quantitative output.
• Scenario Pathway Analysis: This framework complements the scoring model by building a narrative of how an outcome could occur. Instead of just scoring factors in isolation, you will construct the step-by-step sequence of events required for a launch in Q1 versus Q2. This is crucial for checking the logical and temporal feasibility of your quantitative scores. A high score is meaningless if the required events cannot physically happen in the allotted time.

To ensure the discussion is based on the latest information, we will begin with a quick web search before convening the expert panel.

A. Web Search Plan

The purpose of this search is to provide all expert personas with the most up-to-the-minute facts, ensuring the debate is grounded in the current reality as of January 2026.

B. User Research: Expert Roundtable Discussion

• Recommended Method: Discussion (discussionChat)

• Rationale: Your core challenge is to synthesize conflicting expert viewpoints on a complex forecast. A roundtable discussion is the ideal format because it forces these viewpoints to collide, defend, and reconcile in real-time. Observing how a tech optimist debates a regulatory realist, or how a data scientist challenges broad claims with specific metrics, provides a much deeper insight than isolated interviews. The process of argumentation and concession itself is a key data point. This method is essential for your "minority yields to majority" protocol and for building a consensus-based probability.

• Research Subjects (AI Personas):

  1. The Tech Optimist (ex-Tesla Engineer): Focuses on the rapid, non-linear progress of AI and software. Believes the 10B mile target is achievable and that v14's performance is the primary indicator.
  2. The Regulatory Realist (ex-NHTSA Official): Emphasizes bureaucratic process, legal liability, and the slow pace of governmental approval. Views the NHTSA investigation and California's multi-permit process as major roadblocks.
  3. The Financial Analyst (Wall Street Auto Expert): Analyzes the situation based on market pressure, competitive landscape (e.g., Waymo), and shareholder expectations.
  4. The Legal Skeptic (Liability Lawyer): Highlights the ambiguity of "unsupervised," the risk from the FSD branding lawsuit, and the potential for legal challenges to any launch.
  5. The Data Scientist (AV Validation Expert): Is purely metrics-driven. Focuses on the rate of data accumulation (miles driven), disengagement rates, and the statistical requirements for safety validation.
  6. The Market Strategist (Prediction Market Expert): Interprets the existing 53% and 71% odds, looking for market inefficiencies, herd behavior, or information gaps that could be exploited.

• Discussion Guide: Phased Debate Protocol

This protocol will guide the experts from broad definitions to a specific, actionable conclusion.

• Phase 1: Defining the Target (15 mins)

  • Moderator Prompt: "Welcome, experts. Our first task is to define the finish line. For the purpose of these prediction markets, what specific, observable event constitutes an 'unsupervised FSD launch'? Is it a press release announcing general availability? A software update pushed to over 10,000 non-employee vehicles? Or the start of a paid, geofenced robotaxi service in a new city?"
  • Analysis Purpose: This forces the group to agree on a concrete definition, resolving the 20% "Definition" ambiguity upfront. This ensures everyone is debating the same outcome.

• Phase 2: Factor-by-Factor Scoring (45 mins)

  • Moderator Prompt: "Now, we will use our weighted model (Regulatory 40%, Technical 25%, Definition 20%, Credibility 15%) to score the two timelines. We will debate each factor and assign a probability score (0-100%) for each date."
  • Debate Questions:
    1. Regulatory (40% Weight): "Considering the February 23 NHTSA deadline and the separate Texas vs. California pathways, what is the probability of having the minimum necessary regulatory approval for our defined launch by March 31? Now, let's reassess that probability for June 30."
    2. Technical (25% Weight): "Is hitting the 10B mile data target a hard gate? Based on current accumulation rates and v14's performance, what is the probability the technology is validated and ready for our defined launch by March 31? And by June 30?"
    3. Credibility (15% Weight): "How should we factor in Musk's history of optimistic timelines? Does the operational momentum in Texas offset this pattern? Let's assign a confidence score adjustment for the March 31 and June 30 dates based on this."

• Phase 3: Scenario Pathway Construction (20 mins)

  • Moderator Prompt: "Let's move from scores to stories. For a March 31 launch to happen, what is the most plausible sequence of events that must occur, starting from today? (e.g., Favorable NHTSA response, final TxDMV approval, etc.). Now, let's construct the pathway for a June 30 launch. Which of these two narratives is more credible and has fewer dependencies?"
  • Analysis Purpose: This is a qualitative check on the quantitative scores. It helps identify if a high-scoring timeline is logistically impossible due to the number of sequential steps required.

• Phase 4: Synthesis & Consensus (10 mins)

  • Moderator Prompt: "The weighted scores will now be calculated. We will then debate the final numbers. Based on our 'minority yields to majority' protocol, any experts whose views diverge significantly from the calculated consensus will have a final opportunity to argue their case before we establish the group's official fundamental probability."

Part 2: Information Analysis Plan

After the discussion, you will synthesize the collected data to build your investment thesis. Here is how to use the information from each phase to construct your final output.

1. Calculate the Fundamental Probability:

   • How-to: For each date (March 31 and June 30), take the probability scores (0-100%) the experts assigned to each factor during Phase 2 and multiply them by their predefined weights.
   • Formula: P(Launch Date) = (Regulatory Score * 0.40) + (Technical Score * 0.25) + (Definition Score * 0.20) + (Credibility Score * 0.15)
   • This will give you a single, defensible probability number for each market (e.g., "Our analysis yields a 40% probability for March 31 and an 80% probability for June 30").

2. Identify Mispricing & Formulate Recommendation:

   • How-to: Compare your calculated fundamental probability directly against the market odds.
   • Example: "The market implies a 71% chance for a June 30 launch, but our fundamental analysis indicates an 80% probability. This 9-point positive gap suggests the market is underpriced. Conversely, the market implies a 53% chance for March 31, while our analysis shows only 40%. This 13-point negative gap suggests the market is overpriced."
   • Action: This analysis directly translates into your investment recommendation: "The primary recommendation is to buy 'Yes' on the June 30 contract and/or 'No' on the March 31 contract, as this is where our analysis shows the market is most mispriced."

3. Define Key Monitoring Triggers:

   • How-to: Review the transcript of the expert discussion, paying close attention to the "Regulatory" and "Technical" debates in Phase 2. Isolate the specific events that the experts identified as the biggest "if-then" conditions.
   • Example Output: "The top 3 monitoring triggers identified are:
     1. The specific language in Tesla's response to the NHTSA on Feb 23. (Did they provide full data? Was the tone cooperative or defensive?)
     2. An official announcement of final, statewide driverless deployment approval from the Texas Department of Motor Vehicles (TxDMV).
     3. A company or credible third-party announcement that Tesla's FSD fleet has surpassed 9.5 billion cumulative miles."

By following this structured approach, you will produce a robust and well-reasoned investment thesis that goes far beyond a simple guess, providing your client with a clear rationale for action.

Discussion completed. 6 participants discussed.

Discussion Summary: Where agreement clustered (consensus = validated insight)

• Market-resolution practicality over legal/regulatory purity

  • Majority consensus (Alex "Quant" Thorne, ElectroVisionary, Visionary Vance, Dr. Lena Sharma, Arthur Vance) coalesced around a definition that privileges an observable, unambiguous Tesla action as the market trigger: a wide public FSD software release to general customers across North America, accompanied by an explicit, unambiguous Tesla statement declaring the system capable of unsupervised operation without geofencing. Concrete examples:
    • Alex: emphasized that Polymarket-style markets exclude regulatory permits and need tangible, observable events (public release or announcement) for clear resolution.
    • ElectroVisionary & Visionary Vance: argued Tesla historically signals via wide OTA rollouts + high-profile Elon statements rather than waiting for regulatory paperwork.
    • Arthur: agreed to the market-facing definition so long as legal caveats are explicitly stated.
  • Legal-disclaimer framing accepted for market use:
    • Arthur proposed and Alex drafted wording that the panel adopted: the market trigger is Tesla’s public release + declaration, and explicitly “this definition is solely for the purpose of market resolution and carries no legal weight regarding actual autonomous capability, regulatory approval, or liability.” This framing was accepted by the five-majority participants as the operational consensus for forecasting and market resolution.

• Forecasting Tesla’s actions, not validating safety

  • Dr. Lena Sharma accepted (for this exercise) forecasting the probability Tesla will claim and push an unsupervised-capable FSD release, rather than forecasting independent technical validation. Example: Dr. Sharma insisted on statistical validation for true capability but agreed to work with the market-oriented trigger.

Where disagreement occurred (tension = segmentation / risk)

• Regulatory certification vs. manufacturer claim

  • David Safeguard (Regulatory Realist) was the clear dissenter: he insisted that genuine “unsupervised” capability should be defined by regulatory approval or independent safety validation (Level 4/5 certification), not a manufacturer’s claim. Concrete example: David requested “publicly verifiable commitment to an independent, third-party safety audit” as part of the threshold.
  • Tension point: Polymarket’s explicit exclusion of regulatory approvals from resolution (noted by Alex) created fundamental friction: market clarity vs. public safety/regulatory legitimacy.
  • Legal risk concern from Arthur and David: although Arthur accepted the market definition for forecasting, he emphasized that it creates legal and public-safety exposure in reality; David refused to yield on public safety grounds and formally registered dissent.

• Interpretation of “unsupervised” and evidentiary standards

  • Dr. Lena Sharma pushed for data-driven metrics (e.g., failure rates per billion miles, independent audit, defined ODD) to distinguish true unsupervised operation from marketing claims. Example: she demanded “statistically significant evidence of near-zero safety-critical interventions over billions of miles” for true validation.
  • Visionary Vance and ElectroVisionary favored pragmatic, observable business signals (wide OTA release + Elon statement) as operationally decisive for a market. Concrete contrast: Dr. Sharma’s insistence on auditable statistical evidence vs. Visionary Vance’s expectation of Tesla announcing and deploying first, then defending with internal data.

Did anyone change position? (persuasion = messaging opportunity)

• Dr. Lena Sharma: moved from strictly requiring statistical/independent validation for any meaningful “unsupervised” claim to accepting the market-definition for the purposes of forecasting. Reason: pragmatic alignment with the market’s need for an observable trigger and recognition that the panel’s remit is forecasting Tesla’s action rather than validating safety.

  • Example: She explicitly stated she would “work with Alex’s proposed definition” for the forecasting exercise, while reiterating the difference between forecasting Tesla’s claim and verifying technical safety.

• Arthur Vance: initially emphasized strict legal ambiguity and risk; he accepted the market-definition operationally but insisted on explicit legal disclaimers to mitigate conflation of market resolution with legal liability. Reason: preserve legal clarity while enabling the forecasting exercise.

  • Example: Arthur proposed the legal-framework caveat and accepted the majority definition for the market provided the language makes no legal claims.

• David Safeguard: Did not change his core stance. He moved only to formally record his dissent while recognizing the panel must proceed (minority yields to majority protocol). Reason: persistent safety/regulatory concerns and refusal to treat manufacturer claims as a surrogate for independent proof.

Unexpected themes that emerged (emergence = innovation opportunity)

• Formal separation of market resolution triggers from regulatory/technical validation as an explicit policy instrument

  • The group created and explicitly endorsed (in practice) a two-track understanding: (A) market resolution trigger = Tesla’s public claim + wide release; (B) independent/regulatory validation = separate domain that still matters for public safety. Concrete example: Arthur’s legal caveat and Alex’s resolution wording purposefully split legal/regulatory validity from market trigger.
  • Potential innovation opportunity: standardizing a market-focused trigger template that always carries an explicit disclaimer separating resolution from certification—useful for prediction markets dealing with regulated technologies.

• Explicit mention of Polymarket rules materially changed definitional choices

  • Alex’s reminder that Polymarket excludes regulatory approvals reframed the whole Phase 1 debate from “what regulators will approve?” to “what observable Tesla action would actually resolve markets?” Example: this rule pivot forced David’s safety-first framing into a minority view for this exercise.

• Recognition of divergent audiences and evidentiary expectations

  • Two distinct audiences surfaced: market participants (need observable, fast-to-resolve events) vs. regulators/public safety stakeholders (need independent audits and certification). Example: Alex and Visionary Vance prioritized market-observable signals; David and Dr. Sharma prioritized independent verification and rigorous metrics. This bifurcation highlights communication/PR risk for Tesla and potential arbitrage for traders who understand both frames.

Concrete examples cited for each pattern

• Market-resolution practicality: Alex’s explicit Polymarket exclusion of regulatory permits; ElectroVisionary and Visionary Vance’s emphasis on OTA rollouts and Elon announcements as precedent.
• Regulatory/legal concerns: David’s insistence on Level 4/5 certification and third-party audits; Arthur’s insistence on legal disclaimers and note about potential dealer-license suspension risk in California from the December 2025 ruling.
• Technical validation requirements: Dr. Sharma’s call for “failure rates per billion miles with robust confidence intervals” and “statistically significant evidence of near-zero safety-critical interventions.”
• Minority dissent: David formally registered his dissent rather than yielding his safety-first principle.

Summary of the final consensus definition and the dissent

• Consensus definition adopted for forecasting / market resolution:
  • “Resolution occurs upon a wide public FSD software release of Tesla’s Full Self-Driving to general customers across North America, accompanied by an explicit, unambiguous public statement from Tesla declaring the system capable of unsupervised operation without geofencing. This definition is solely for the purpose of market resolution and carries no legal weight regarding actual autonomous capability, regulatory approval, or liability.”
  • Supported by: Alex "Quant" Thorne, ElectroVisionary, Visionary Vance, Dr. Lena Sharma, Arthur Vance (majority).
• Formal dissent:
  • David Safeguard (Regulatory Realist) formally registered his opposition, arguing the definition accepts unverified manufacturer claims and could mislead the public; he continued to insist on regulatory or independent safety validation as the correct standard for true “unsupervised” operation.

What this consensus implies for subsequent phases (briefly, evidence-grounding)

• The panel will now produce probability scores forecasting Tesla’s public behavior (claim + wide OTA release) rather than probabilities about independent regulatory approvals or demonstrated safety performance.
• The weighting matrix (Regulatory 40% / Technical 25% / Definition 20% / Credibility 15%) will be applied to estimate the probability Tesla will undertake the agreed market-triggering action by the target dates, but participants disagreed on how to interpret “Regulatory” within that matrix (practical likelihood Tesla can push a release vs. true regulatory clearance).
• The dissenting view remains recorded and must be explicitly noted in any investor-facing communication as a safety/regulatory caveat: the market resolution event is not the same as regulatory certification or verified safe operation.

Documented positions for record (who said what, succinctly)

• Alex "Quant" Thorne: Market-resolution pragmatist; argued for observable public release/announcement as the proper market trigger; provided final suggested wording and cited Polymarket rules excluding regulatory approvals.
• ElectroVisionary: Industry POV; recommended definition focusing on wide OTA release + Elon statement as the most unambiguous market signal.
• Visionary Vance (Tech Optimist): Expected Tesla to announce & deploy via OTA + Elon promotion; viewed regulatory steps as procedural or secondary.
• Dr. Lena Sharma (Data Scientist): Preferred statistical, independently verifiable metrics for authentic unsupervised capability; accepted the market-oriented definition for forecasting purposes while emphasizing the difference between claim and validated performance.
• Arthur Vance (Legal Expert / Moderator role): Insisted on explicit legal disclaimer separating market resolution from legal/regulatory meaning; accepted the majority definition for forecasting so long as legal caveats are included.
• David Safeguard (Regulatory Realist): Rejected market-only definition as insufficient and dangerous; formally recorded dissent, calling for regulatory approval or third-party audit as necessary for a genuine “unsupervised” threshold.

Closing note on how to use this summary

• This summary isolates the points of consensus that will drive the probability scoring (Tesla’s public claim + wide OTA release as the market trigger) and documents the key dissenting safety/regulatory argument to ensure transparency.
• The majority clarified that subsequent probability scoring is a forecast of Tesla’s public actions (announcement + release) within the defined timeframe and not a claim about validated safety or regulatory compliance; David’s dissent remains formally recorded as a distinct, substantive objection grounded in public-safety and legal concerns.